From 9c0e25d137115631d0e11ca4f5c151b5bbdcec43 Mon Sep 17 00:00:00 2001 From: Ruangrin L <88072261+idalr@users.noreply.github.com> Date: Fri, 17 Nov 2023 17:24:36 +0100 Subject: [PATCH 01/29] import and create files --- dataset_builders/pie/argmicro/argmicro.py | 283 +++++++++ .../pie/argmicro/requirements.txt | 1 + tests/dataset_builders/pie/test_argmicro.py | 563 ++++++++++++++++++ .../arg-microtexts-master.zip | Bin 0 -> 2964901 bytes .../hf/argmicro/de.train.0.json | 21 + .../hf/argmicro/en.train.0.json | 21 + 6 files changed, 889 insertions(+) create mode 100644 dataset_builders/pie/argmicro/argmicro.py create mode 100644 dataset_builders/pie/argmicro/requirements.txt create mode 100644 tests/dataset_builders/pie/test_argmicro.py create mode 100644 tests/fixtures/dataset_builders/arg-microtexts-master.zip create mode 100644 tests/fixtures/dataset_builders/hf/argmicro/de.train.0.json create mode 100644 tests/fixtures/dataset_builders/hf/argmicro/en.train.0.json diff --git a/dataset_builders/pie/argmicro/argmicro.py b/dataset_builders/pie/argmicro/argmicro.py new file mode 100644 index 00000000..11770bd5 --- /dev/null +++ b/dataset_builders/pie/argmicro/argmicro.py @@ -0,0 +1,283 @@ +import dataclasses +import logging +from collections import defaultdict +from typing import Any, Callable, Dict, List, Optional, Tuple + +import datasets +from pytorch_ie.annotations import Span +from pytorch_ie.core import Annotation, AnnotationList, annotation_field +from pytorch_ie.documents import ( + TextBasedDocument, + TextDocumentWithLabeledSpansAndBinaryRelations, +) + +from pie_datasets import GeneratorBasedBuilder + +log = logging.getLogger(__name__) + + +def dl2ld(dict_of_lists): + return [dict(zip(dict_of_lists, t)) for t in zip(*dict_of_lists.values())] + + +def ld2dl(list_of_dicts, keys: Optional[List[str]] = None, as_list: bool = False): + if keys is None: + keys = list_of_dicts[0].keys() + if as_list: + return [[d[k] for d in list_of_dicts] for k in keys] + else: + return {k: [d[k] for d in list_of_dicts] for k in keys} + + +@dataclasses.dataclass(frozen=True) +class LabeledAnnotationCollection(Annotation): + annotations: Tuple[Annotation, ...] + label: str + + +@dataclasses.dataclass(frozen=True) +class MultiRelation(Annotation): + heads: Tuple[Annotation, ...] # sources == heads + tails: Tuple[Annotation, ...] # targets == tails + label: str + + +@dataclasses.dataclass +class ArgMicroDocument(TextBasedDocument): + topic_id: Optional[str] = None + stance: Optional[str] = None + edus: AnnotationList[Span] = annotation_field(target="text") + adus: AnnotationList[LabeledAnnotationCollection] = annotation_field(target="edus") + relations: AnnotationList[MultiRelation] = annotation_field(target="adus") + + +def example_to_document( + example: Dict[str, Any], + adu_type_int2str: Callable[[int], str], + edge_type_int2str: Callable[[int], str], + stance_int2str: Callable[[int], str], +) -> ArgMicroDocument: + stance = stance_int2str(example["stance"]) + document = ArgMicroDocument( + id=example["id"], + text=example["text"], + topic_id=example["topic_id"] if example["topic_id"] != "UNDEFINED" else None, + stance=stance if stance != "UNDEFINED" else None, + ) + # build EDUs + edus_dict = { + edu["id"]: Span(start=edu["start"], end=edu["end"]) for edu in dl2ld(example["edus"]) + } + # build ADUs + adu_id2edus = defaultdict(list) + edges_multi_source = defaultdict(dict) + for edge in dl2ld(example["edges"]): + edge_type = edge_type_int2str(edge["type"]) + if edge_type == "seg": + adu_id2edus[edge["trg"]].append(edus_dict[edge["src"]]) + elif edge_type == "add": + if "src" not in edges_multi_source[edge["trg"]]: + edges_multi_source[edge["trg"]]["src"] = [] + edges_multi_source[edge["trg"]]["src"].append(edge["src"]) + else: + edges_multi_source[edge["id"]]["type"] = edge_type + edges_multi_source[edge["id"]]["trg"] = edge["trg"] + if "src" not in edges_multi_source[edge["id"]]: + edges_multi_source[edge["id"]]["src"] = [] + edges_multi_source[edge["id"]]["src"].append(edge["src"]) + adus_dict = {} + for adu in dl2ld(example["adus"]): + adu_type = adu_type_int2str(adu["type"]) + adu_edus = adu_id2edus[adu["id"]] + adus_dict[adu["id"]] = LabeledAnnotationCollection( + annotations=tuple(adu_edus), label=adu_type + ) + # build relations + rels_dict = {} + for edge_id, edge in edges_multi_source.items(): + edge_target = edge["trg"] + if edge_target in edges_multi_source: + targets = edges_multi_source[edge_target]["src"] + else: + targets = [edge_target] + if any(target in edges_multi_source for target in targets): + raise Exception("Multi-hop relations are not supported") + rel = MultiRelation( + heads=tuple(adus_dict[source] for source in edge["src"]), + tails=tuple(adus_dict[target] for target in targets), + label=edge["type"], + ) + rels_dict[edge_id] = rel + + document.edus.extend(edus_dict.values()) + document.adus.extend(adus_dict.values()) + document.relations.extend(rels_dict.values()) + document.metadata["edu_ids"] = list(edus_dict.keys()) + document.metadata["adu_ids"] = list(adus_dict.keys()) + document.metadata["rel_ids"] = list(rels_dict.keys()) + + document.metadata["rel_seg_ids"] = { + edge["src"]: edge["id"] + for edge in dl2ld(example["edges"]) + if edge_type_int2str(edge["type"]) == "seg" + } + document.metadata["rel_add_ids"] = { + edge["src"]: edge["id"] + for edge in dl2ld(example["edges"]) + if edge_type_int2str(edge["type"]) == "add" + } + return document + + +def document_to_example( + document: ArgMicroDocument, + adu_type_str2int: Callable[[str], int], + edge_type_str2int: Callable[[str], int], + stance_str2int: Callable[[str], int], +) -> Dict[str, Any]: + result = { + "id": document.id, + "text": document.text, + "topic_id": document.topic_id or "UNDEFINED", + "stance": stance_str2int(document.stance or "UNDEFINED"), + } + + # construct EDUs + edus = { + edu: {"id": edu_id, "start": edu.start, "end": edu.end} + for edu_id, edu in zip(document.metadata["edu_ids"], document.edus) + } + result["edus"] = ld2dl( + sorted(edus.values(), key=lambda x: x["id"]), keys=["id", "start", "end"] + ) + + # construct ADUs + adus = { + adu: {"id": adu_id, "type": adu_type_str2int(adu.label)} + for adu_id, adu in zip(document.metadata["adu_ids"], document.adus) + } + result["adus"] = ld2dl(sorted(adus.values(), key=lambda x: x["id"]), keys=["id", "type"]) + + # construct edges + rels_dict: Dict[str, MultiRelation] = { + rel_id: rel for rel_id, rel in zip(document.metadata["rel_ids"], document.relations) + } + heads2rel_id = { + rel.heads: red_id for red_id, rel in zip(document.metadata["rel_ids"], document.relations) + } + edges = [] + for rel_id, rel in rels_dict.items(): + # if it is an undercut attack, we need to change the target to the relation that connects the target + if rel.label == "und": + target_id = heads2rel_id[rel.tails] + else: + if len(rel.tails) > 1: + raise Exception("Multi-target relations are not supported") + target_id = adus[rel.tails[0]]["id"] + source_id = adus[rel.heads[0]]["id"] + edge = { + "id": rel_id, + "src": source_id, + "trg": target_id, + "type": edge_type_str2int(rel.label), + } + edges.append(edge) + # if it is an additional support, we need to change the source to the relation that connects the source + for head in rel.heads[1:]: + source_id = adus[head]["id"] + edge_id = document.metadata["rel_add_ids"][source_id] + edge = { + "id": edge_id, + "src": source_id, + "trg": rel_id, + "type": edge_type_str2int("add"), + } + edges.append(edge) + + for adu_id, adu in zip(document.metadata["adu_ids"], document.adus): + for edu in adu.annotations: + source_id = edus[edu]["id"] + target_id = adus[adu]["id"] + edge_id = document.metadata["rel_seg_ids"][source_id] + edge = { + "id": edge_id, + "src": source_id, + "trg": target_id, + "type": edge_type_str2int("seg"), + } + edges.append(edge) + + result["edges"] = ld2dl( + sorted(edges, key=lambda x: x["id"]), keys=["id", "src", "trg", "type"] + ) + return result + + +def convert_to_text_document_with_labeled_spans_and_binary_relations( + doc: ArgMicroDocument, +) -> TextDocumentWithLabeledSpansAndBinaryRelations: + # convert adus to entities + entities = [] + adu2entity: Dict[LabeledAnnotationCollection, Span] = {} + for adu in doc.adus: + edus: Set[Span] = set(adu.annotations) + start = min(edu.start for edu in edus) + end = max(edu.end for edu in edus) + # assert there are no edus overlapping with the adu, but not part of it + for edu in doc.edus: + if (start <= edu.start < end or start < edu.end <= end) and edu not in edus: + raise Exception(f"edu {edu} is overlapping with adu {adu}, but is not part of it") + entity = LabeledSpan(start=start, end=end, label=adu.label) + entities.append(entity) + adu2entity[adu] = entity + relations = [] + for relation in doc.relations: + # add all possible combinations of heads and tails + for head in relation.heads: + for tail in relation.tails: + rel = BinaryRelation( + label=relation.label, head=adu2entity[head], tail=adu2entity[tail] + ) + relations.append(rel) + # also add the relations between the heads themselves + for head1, head2 in combinations(relation.heads, 2): + rel = BinaryRelation(label="joint", head=adu2entity[head1], tail=adu2entity[head2]) + relations.append(rel) + # also add the reverse relation + rel = BinaryRelation(label="joint", head=adu2entity[head2], tail=adu2entity[head1]) + relations.append(rel) + + metadata = dict(doc.metadata) + metadata["stance"] = doc.stance + metadata["topic"] = doc.topic_id + result = TextDocumentWithLabeledSpansAndBinaryRelations( + text=doc.text, id=doc.id, metadata=doc.metadata + ) + result.labeled_spans.extend(entities) + result.binary_relations.extend(relations) + + return result + + +class ArgMicro(GeneratorBasedBuilder): + DOCUMENT_TYPE = ArgMicroDocument + + BASE_DATASET_PATH = "DFKI-SLT/argmicro" + BASE_DATASET_REVISION = "22958d585f5c0c646c81ac62947bdf6cf9ab3cc5" + + BUILDER_CONFIGS = [datasets.BuilderConfig(name="en"), datasets.BuilderConfig(name="de")] + + def _generate_document_kwargs(self, dataset): + return { + "adu_type_int2str": dataset.features["adus"].feature["type"].int2str, + "edge_type_int2str": dataset.features["edges"].feature["type"].int2str, + "stance_int2str": dataset.features["stance"].int2str, + } + + def _generate_document(self, example, adu_type_int2str, edge_type_int2str, stance_int2str): + return example_to_document( + example, + adu_type_int2str=adu_type_int2str, + edge_type_int2str=edge_type_int2str, + stance_int2str=stance_int2str, + ) diff --git a/dataset_builders/pie/argmicro/requirements.txt b/dataset_builders/pie/argmicro/requirements.txt new file mode 100644 index 00000000..738010cb --- /dev/null +++ b/dataset_builders/pie/argmicro/requirements.txt @@ -0,0 +1 @@ +pie-datasets>=0.3.3 diff --git a/tests/dataset_builders/pie/test_argmicro.py b/tests/dataset_builders/pie/test_argmicro.py new file mode 100644 index 00000000..d1932a83 --- /dev/null +++ b/tests/dataset_builders/pie/test_argmicro.py @@ -0,0 +1,563 @@ +import json +from collections import Counter +from typing import List + +import pytest +from datasets import disable_caching, load_dataset +from pytorch_ie.core import Document +from pytorch_ie.documents import ( + TextBasedDocument, + TextDocumentWithLabeledSpansAndBinaryRelations, +) +from transformers import AutoTokenizer, PreTrainedTokenizer + +from dataset_builders.pie.argmicro.argmicro import ( + ArgMicro, + ArgMicroDocument, + convert_to_text_document_with_labeled_spans_and_binary_relations, + document_to_example, + example_to_document, +) +from pie_datasets import DatasetDict +from pie_datasets.document.conversion import tokenize_document +from pie_datasets.document.types import TokenDocumentWithLabeledSpansAndBinaryRelations +from tests import FIXTURES_ROOT +from tests.dataset_builders.common import HF_DS_FIXTURE_DATA_PATH, PIE_BASE_PATH + +disable_caching() + +DATASET_NAME = "argmicro" +SPLIT_SIZES = {"train": 112} +DATA_PATH = FIXTURES_ROOT / "dataset_builders" / "arg-microtexts-master.zip" +HF_DATASET_PATH = ArgMicro.BASE_DATASET_PATH +PIE_DATASET_PATH = PIE_BASE_PATH / DATASET_NAME + + +@pytest.fixture(scope="module", params=["en", "de"]) +def language(request): + return request.param + + +@pytest.fixture(scope="module") +def hf_dataset(language): + return load_dataset(str(HF_DATASET_PATH), name=language, data_dir=DATA_PATH) + + +@pytest.fixture(scope="module") +def adu_type_int2str(hf_dataset): + ds = hf_dataset["train"] + return ds.features["adus"].feature["type"].int2str + + +@pytest.fixture(scope="module") +def edge_type_int2str(hf_dataset): + ds = hf_dataset["train"] + return ds.features["edges"].feature["type"].int2str + + +@pytest.fixture(scope="module") +def stance_int2str(hf_dataset): + ds = hf_dataset["train"] + return ds.features["stance"].int2str + + +def test_hf_dataset(hf_dataset, language, adu_type_int2str, edge_type_int2str, stance_int2str): + assert hf_dataset is not None + assert {name: len(ds) for name, ds in hf_dataset.items()} == SPLIT_SIZES + ds = hf_dataset["train"] + # check + topic_id_values = Counter([ex["topic_id"] for ex in ds]) + stance_values = Counter([stance_int2str(ex["stance"]) for ex in ds]) + adu_type_values = Counter() + edge_type_values = Counter() + for ex in ds: + adu_type_values.update([adu_type_int2str(t) for t in ex["adus"]["type"]]) + edge_type_values.update([edge_type_int2str(t) for t in ex["edges"]["type"]]) + assert dict(topic_id_values) == { + "UNDEFINED": 23, + "higher_dog_poo_fines": 9, + "health_insurance_cover_complementary_medicine": 8, + "introduce_capital_punishment": 8, + "allow_shops_to_open_on_holidays_and_sundays": 8, + "public_broadcasting_fees_on_demand": 7, + "over_the_counter_morning_after_pill": 6, + "cap_rent_increases": 6, + "charge_tuition_fees": 6, + "keep_retirement_at_63": 6, + "stricter_regulation_of_intelligence_services": 4, + "increase_weight_of_BA_thesis_in_final_grade": 4, + "school_uniforms": 3, + "make_video_games_olympic": 3, + "EU_influence_on_political_events_in_Ukraine": 3, + "TXL_airport_remain_operational_after_BER_opening": 3, + "buy_tax_evader_data_from_dubious_sources": 2, + "partial_housing_development_at_Tempelhofer_Feld": 2, + "waste_separation": 1, + } + assert dict(stance_values) == {"pro": 46, "con": 42, "UNDEFINED": 23, "unclear": 1} + assert dict(adu_type_values) == {"pro": 451, "opp": 125} + assert dict(edge_type_values) == { + "seg": 576, + "sup": 263, + "reb": 108, + "und": 63, + "add": 21, + "exa": 9, + } + + +@pytest.fixture +def hf_example(hf_dataset): + return hf_dataset["train"][0] + + +def test_hf_example( + hf_example, hf_dataset, language, adu_type_int2str, edge_type_int2str, stance_int2str +): + fixture_path = HF_DS_FIXTURE_DATA_PATH / DATASET_NAME / f"{language}.train.0.json" + # hf_example_expected = json.loads(fixture_path.read_text()) + hf_example_expected = json.loads(open(fixture_path, encoding="utf-8").read()) + assert hf_example == hf_example_expected + assert stance_int2str(hf_example["stance"]) == "pro" + assert [adu_type_int2str(t) for t in hf_example["adus"]["type"]] == [ + "opp", + "opp", + "pro", + "pro", + "pro", + ] + assert [edge_type_int2str(t) for t in hf_example["edges"]["type"]] == [ + "reb", + "seg", + "sup", + "und", + "add", + "seg", + "seg", + "seg", + "seg", + ] + + +def test_example_to_document( + hf_example, adu_type_int2str, edge_type_int2str, stance_int2str, language +): + doc = example_to_document( + hf_example, + adu_type_int2str=adu_type_int2str, + edge_type_int2str=edge_type_int2str, + stance_int2str=stance_int2str, + ) + assert doc is not None + assert doc.id == "micro_b001" + assert doc.topic_id == "waste_separation" + assert doc.stance == "pro" + assert len(doc.edus) == 5 + assert doc.metadata["edu_ids"] == ["e1", "e2", "e3", "e4", "e5"] + edus_dict = {edu_id: edu for edu_id, edu in zip(doc.metadata["edu_ids"], doc.edus)} + if language == "en": + assert ( + str(doc.edus[0]) + == "Yes, it's annoying and cumbersome to separate your rubbish properly all the time." + ) + assert ( + str(doc.edus[1]) + == "Three different bin bags stink away in the kitchen and have to be sorted into different wheelie bins." + ) + assert str(doc.edus[2]) == "But still Germany produces way too much rubbish" + assert ( + str(doc.edus[3]) + == "and too many resources are lost when what actually should be separated and recycled is burnt." + ) + assert ( + str(doc.edus[4]) + == "We Berliners should take the chance and become pioneers in waste separation!" + ) + elif language == "de": + # we don't check this because spellcheck would complain + pass + else: + raise ValueError(f"Unknown language {language}") + + assert len(doc.adus) == 5 + assert doc.metadata["adu_ids"] == ["a1", "a2", "a3", "a4", "a5"] + adus_dict = {adu_id: adu for adu_id, adu in zip(doc.metadata["adu_ids"], doc.adus)} + assert doc.adus[0].label == "opp" + assert len(doc.adus[0].annotations) == 1 + assert doc.adus[0].annotations[0] == doc.edus[0] + assert doc.adus[1].label == "opp" + assert len(doc.adus[1].annotations) == 1 + assert doc.adus[1].annotations[0] == doc.edus[1] + assert doc.adus[2].label == "pro" + assert len(doc.adus[2].annotations) == 1 + assert doc.adus[2].annotations[0] == doc.edus[2] + assert doc.adus[3].label == "pro" + assert len(doc.adus[3].annotations) == 1 + assert doc.adus[3].annotations[0] == doc.edus[3] + assert doc.adus[4].label == "pro" + assert len(doc.adus[4].annotations) == 1 + assert doc.adus[4].annotations[0] == doc.edus[4] + + # sources == heads + # targets == tails + assert len(doc.relations) == 3 + assert doc.metadata["rel_ids"] == ["c1", "c2", "c3"] + rels_dict = {rel_id: rel for rel_id, rel in zip(doc.metadata["rel_ids"], doc.relations)} + + rel = rels_dict["c1"] + assert rel.label == "reb" # rebutting attack + assert len(rel.heads) == 1 + assert rel.heads[0] == adus_dict["a1"] + assert len(rel.tails) == 1 + assert rel.tails[0] == adus_dict["a5"] + + rel = rels_dict["c2"] + assert rel.label == "sup" # support + assert len(rel.heads) == 1 + assert rel.heads[0] == adus_dict["a2"] + assert len(rel.tails) == 1 + assert rel.tails[0] == adus_dict["a1"] + + rel = rels_dict["c3"] + assert rel.label == "und" # undercutting attack + assert len(rel.heads) == 2 + assert rel.heads[0] == adus_dict["a3"] + assert rel.heads[1] == adus_dict["a4"] + assert len(rel.tails) == 1 + assert rel.tails[0] == adus_dict["a1"] + + assert doc.metadata["rel_seg_ids"] == { + "e1": "c6", + "e2": "c7", + "e3": "c8", + "e4": "c9", + "e5": "c10", + } + assert doc.metadata["rel_add_ids"] == {"a4": "c4"} + + +@pytest.fixture(scope="module") +def adu_type_str2int(hf_dataset): + ds = hf_dataset["train"] + return ds.features["adus"].feature["type"].str2int + + +@pytest.fixture(scope="module") +def edge_type_str2int(hf_dataset): + ds = hf_dataset["train"] + return ds.features["edges"].feature["type"].str2int + + +@pytest.fixture(scope="module") +def stance_str2int(hf_dataset): + ds = hf_dataset["train"] + return ds.features["stance"].str2int + + +def test_example_to_document_and_back( + hf_example, + adu_type_int2str, + edge_type_int2str, + adu_type_str2int, + edge_type_str2int, + stance_int2str, + stance_str2int, +): + doc = example_to_document( + hf_example, + adu_type_int2str=adu_type_int2str, + edge_type_int2str=edge_type_int2str, + stance_int2str=stance_int2str, + ) + hf_example_back = document_to_example( + doc, + adu_type_str2int=adu_type_str2int, + edge_type_str2int=edge_type_str2int, + stance_str2int=stance_str2int, + ) + assert hf_example == hf_example_back + + +def test_example_to_document_and_back_all( + hf_dataset, + adu_type_int2str, + edge_type_int2str, + adu_type_str2int, + edge_type_str2int, + stance_int2str, + stance_str2int, +): + for ex in hf_dataset["train"]: + doc = example_to_document( + ex, + adu_type_int2str=adu_type_int2str, + edge_type_int2str=edge_type_int2str, + stance_int2str=stance_int2str, + ) + ex_back = document_to_example( + doc, + adu_type_str2int=adu_type_str2int, + edge_type_str2int=edge_type_str2int, + stance_str2int=stance_str2int, + ) + assert ex == ex_back + + +import datasets + + +@pytest.fixture(scope="module") +def dataset() -> DatasetDict: + return DatasetDict.load_dataset(path=str(PIE_DATASET_PATH), name="en") + + +def test_dataset(dataset): + assert dataset is not None + assert {name: len(ds) for name, ds in dataset.items()} == SPLIT_SIZES + + +@pytest.fixture(scope="module") +def document(dataset) -> ArgMicroDocument: + doc = dataset["train"][0] + # we can not assert the real document type because it may come from a dataset loading script + # downloaded to a temporary directory and thus have a different type object, although it is + # semantically the same + assert isinstance(doc, Document) + return doc + + +@pytest.fixture(scope="module") +def tokenizer() -> PreTrainedTokenizer: + return AutoTokenizer.from_pretrained("bert-base-uncased") + + +@pytest.fixture(scope="module") +def dataset_of_text_documents_with_labeled_spans_and_binary_relations( + dataset, +) -> DatasetDict: + converted_dataset = dataset.to_document_type(TextDocumentWithLabeledSpansAndBinaryRelations) + return converted_dataset + + +def test_convert_to_textdocument_with_entities_and_relations( + document, dataset_of_text_documents_with_labeled_spans_and_binary_relations +): + # just check that we get the same as in the converted dataset when explicitly calling the conversion method + converted_doc = convert_to_text_document_with_labeled_spans_and_binary_relations(document) + doc_from_converted_dataset = dataset_of_text_documents_with_labeled_spans_and_binary_relations[ + "train" + ][0] + assert converted_doc == doc_from_converted_dataset + + +def test_dataset_of_text_documents_with_labeled_spans_and_binary_relations( + dataset_of_text_documents_with_labeled_spans_and_binary_relations, +): + assert dataset_of_text_documents_with_labeled_spans_and_binary_relations is not None + # get a document to check + converted_doc = dataset_of_text_documents_with_labeled_spans_and_binary_relations["train"][0] + + assert isinstance(converted_doc, TextDocumentWithLabeledSpansAndBinaryRelations) + assert len(converted_doc.labeled_spans) == 5 + + # check the entities + entity_tuples = [(str(ent), ent.label) for ent in converted_doc.labeled_spans] + assert entity_tuples[0] == ( + "Yes, it's annoying and cumbersome to separate your rubbish properly all the time.", + "opp", + ) + assert entity_tuples[1] == ( + "Three different bin bags stink away in the kitchen and have to be sorted into different wheelie bins.", + "opp", + ) + assert entity_tuples[2] == ("But still Germany produces way too much rubbish", "pro") + assert entity_tuples[3] == ( + "and too many resources are lost when what actually should be separated and recycled is burnt.", + "pro", + ) + assert entity_tuples[4] == ( + "We Berliners should take the chance and become pioneers in waste separation!", + "pro", + ) + + # check the relations + relation_tuples = [ + (str(rel.head), rel.label, str(rel.tail)) for rel in converted_doc.binary_relations + ] + assert len(relation_tuples) == 6 + assert relation_tuples[0] == ( + "Yes, it's annoying and cumbersome to separate your rubbish properly all the time.", + "reb", + "We Berliners should take the chance and become pioneers in waste separation!", + ) + assert relation_tuples[1] == ( + "Three different bin bags stink away in the kitchen and have to be sorted into different wheelie bins.", + "sup", + "Yes, it's annoying and cumbersome to separate your rubbish properly all the time.", + ) + # Note: originally, the "undercut" relation has a joint head, + # but we split it into two relations ... + assert relation_tuples[2] == ( + "But still Germany produces way too much rubbish", + "und", + "Yes, it's annoying and cumbersome to separate your rubbish properly all the time.", + ) + assert relation_tuples[3] == ( + "and too many resources are lost when what actually should be separated and recycled is burnt.", + "und", + "Yes, it's annoying and cumbersome to separate your rubbish properly all the time.", + ) + # ... and link the heads with "joint" relations in a symmetric fashion + assert relation_tuples[4] == ( + "But still Germany produces way too much rubbish", + "joint", + "and too many resources are lost when what actually should be separated and recycled is burnt.", + ) + assert relation_tuples[5] == ( + "and too many resources are lost when what actually should be separated and recycled is burnt.", + "joint", + "But still Germany produces way too much rubbish", + ) + + +@pytest.fixture(scope="module") +def tokenized_documents_with_labeled_spans_and_binary_relations( + dataset_of_text_documents_with_labeled_spans_and_binary_relations, tokenizer +) -> List[TokenDocumentWithLabeledSpansAndBinaryRelations]: + # get a document to check + doc = dataset_of_text_documents_with_labeled_spans_and_binary_relations["train"][0] + # Note, that this is a list of documents, because the document may be split into chunks + # if the input text is too long. + tokenized_docs = tokenize_document( + doc, + tokenizer=tokenizer, + return_overflowing_tokens=True, + result_document_type=TokenDocumentWithLabeledSpansAndBinaryRelations, + verbose=True, + ) + return tokenized_docs + + +def test_tokenized_documents_with_labeled_spans_and_binary_relations( + tokenized_documents_with_labeled_spans_and_binary_relations, +): + docs = tokenized_documents_with_labeled_spans_and_binary_relations + + # check that the tokenization was fine + assert len(docs) == 1 + doc = docs[0] + assert len(doc.tokens) == 81 + assert len(doc.labeled_spans) == 5 + ent = doc.labeled_spans[0] + assert ent.target[ent.start : ent.end] == ( + "yes", + ",", + "it", + "'", + "s", + "annoying", + "and", + "cum", + "##bers", + "##ome", + "to", + "separate", + "your", + "rubbish", + "properly", + "all", + "the", + "time", + ".", + ) + ent = doc.labeled_spans[1] + assert ent.target[ent.start : ent.end] == ( + "three", + "different", + "bin", + "bags", + "stink", + "away", + "in", + "the", + "kitchen", + "and", + "have", + "to", + "be", + "sorted", + "into", + "different", + "wheel", + "##ie", + "bin", + "##s", + ".", + ) + ent = doc.labeled_spans[2] + assert ent.target[ent.start : ent.end] == ( + "but", + "still", + "germany", + "produces", + "way", + "too", + "much", + "rubbish", + ) + ent = doc.labeled_spans[3] + assert ent.target[ent.start : ent.end] == ( + "and", + "too", + "many", + "resources", + "are", + "lost", + "when", + "what", + "actually", + "should", + "be", + "separated", + "and", + "recycled", + "is", + "burnt", + ".", + ) + ent = doc.labeled_spans[4] + assert ent.target[ent.start : ent.end] == ( + "we", + "berlin", + "##ers", + "should", + "take", + "the", + "chance", + "and", + "become", + "pioneers", + "in", + "waste", + "separation", + "!", + ) + + +def test_tokenized_documents_with_entities_and_relations_all( + dataset_of_text_documents_with_labeled_spans_and_binary_relations, tokenizer +): + for split, docs in dataset_of_text_documents_with_labeled_spans_and_binary_relations.items(): + for doc in docs: + # Note, that this is a list of documents, because the document may be split into chunks + # if the input text is too long. + tokenized_docs = tokenize_document( + doc, + tokenizer=tokenizer, + return_overflowing_tokens=True, + result_document_type=TokenDocumentWithLabeledSpansAndBinaryRelations, + verbose=True, + ) + # we just ensure that we get at least one tokenized document + assert tokenized_docs is not None + assert len(tokenized_docs) > 0 diff --git a/tests/fixtures/dataset_builders/arg-microtexts-master.zip b/tests/fixtures/dataset_builders/arg-microtexts-master.zip new file mode 100644 index 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Drei verschiedene Müllbeutel müffeln in der Küche und müssen in drei unterschiedliche Tonnen einsortiert werden. Aber immer noch wird in Deutschland viel zu viel Müll produziert und zu viele Ressourcen gehen verloren, wenn zusammen verbrannt wird, was getrennt eigentlich verwertet werden könnte. Wir Berliner sollten die Chance nutzen und Vorreiter im Mülltrennen werden!", + "edus": { + "id": ["e1", "e2", "e3", "e4", "e5"], + "start": [0, 69, 182, 247, 366], + "end": [68, 181, 246, 365, 441] + }, + "adus": { + "id": ["a1", "a2", "a3", "a4", "a5"], + "type": [0, 0, 1, 1, 1] + }, + "edges": { + "id": ["c1", "c10", "c2", "c3", "c4", "c6", "c7", "c8", "c9"], + "src": ["a1", "e5", "a2", "a3", "a4", "e1", "e2", "e3", "e4"], + "trg": ["a5", "a5", "a1", "c1", "c3", "a1", "a2", "a3", "a4"], + "type": [4, 0, 1, 5, 3, 0, 0, 0, 0] + } +} diff --git a/tests/fixtures/dataset_builders/hf/argmicro/en.train.0.json b/tests/fixtures/dataset_builders/hf/argmicro/en.train.0.json new file mode 100644 index 00000000..56774315 --- /dev/null +++ b/tests/fixtures/dataset_builders/hf/argmicro/en.train.0.json @@ -0,0 +1,21 @@ +{ + "id": "micro_b001", + "topic_id": "waste_separation", + "stance": 1, + "text": "Yes, it's annoying and cumbersome to separate your rubbish properly all the time. Three different bin bags stink away in the kitchen and have to be sorted into different wheelie bins. But still Germany produces way too much rubbish and too many resources are lost when what actually should be separated and recycled is burnt. We Berliners should take the chance and become pioneers in waste separation!", + "edus": { + "id": ["e1", "e2", "e3", "e4", "e5"], + "start": [0, 82, 184, 232, 326], + "end": [81, 183, 231, 325, 402] + }, + "adus": { + "id": ["a1", "a2", "a3", "a4", "a5"], + "type": [0, 0, 1, 1, 1] + }, + "edges": { + "id": ["c1", "c10", "c2", "c3", "c4", "c6", "c7", "c8", "c9"], + "src": ["a1", "e5", "a2", "a3", "a4", "e1", "e2", "e3", "e4"], + "trg": ["a5", "a5", "a1", "c1", "c3", "a1", "a2", "a3", "a4"], + "type": [4, 0, 1, 5, 3, 0, 0, 0, 0] + } +} From 29c72946bbd749c0aa822b2c9829b83b472399d2 Mon Sep 17 00:00:00 2001 From: Ruangrin L <88072261+idalr@users.noreply.github.com> Date: Tue, 21 Nov 2023 10:53:08 +0100 Subject: [PATCH 02/29] check test_argmicro.py file --- dataset_builders/pie/argmicro/argmicro.py | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/dataset_builders/pie/argmicro/argmicro.py b/dataset_builders/pie/argmicro/argmicro.py index 11770bd5..3ab27c7f 100644 --- a/dataset_builders/pie/argmicro/argmicro.py +++ b/dataset_builders/pie/argmicro/argmicro.py @@ -1,10 +1,11 @@ import dataclasses import logging from collections import defaultdict -from typing import Any, Callable, Dict, List, Optional, Tuple +from itertools import combinations +from typing import Any, Callable, Dict, List, Optional, Set, Tuple import datasets -from pytorch_ie.annotations import Span +from pytorch_ie.annotations import BinaryRelation, LabeledSpan, Span from pytorch_ie.core import Annotation, AnnotationList, annotation_field from pytorch_ie.documents import ( TextBasedDocument, @@ -262,6 +263,10 @@ def convert_to_text_document_with_labeled_spans_and_binary_relations( class ArgMicro(GeneratorBasedBuilder): DOCUMENT_TYPE = ArgMicroDocument + DOCUMENT_CONVERTERS = { + TextDocumentWithLabeledSpansAndBinaryRelations: convert_to_text_document_with_labeled_spans_and_binary_relations + } + BASE_DATASET_PATH = "DFKI-SLT/argmicro" BASE_DATASET_REVISION = "22958d585f5c0c646c81ac62947bdf6cf9ab3cc5" From 6feb57dc8bd8a17ee3e52077c2909407dbd2f8e8 Mon Sep 17 00:00:00 2001 From: Ruangrin L <88072261+idalr@users.noreply.github.com> Date: Tue, 21 Nov 2023 14:49:56 +0100 Subject: [PATCH 03/29] edit `_generate_document_kwargs` and created more tests --- dataset_builders/pie/argmicro/argmicro.py | 55 +++-- tests/dataset_builders/pie/test_argmicro.py | 237 +++++++++----------- 2 files changed, 132 insertions(+), 160 deletions(-) diff --git a/dataset_builders/pie/argmicro/argmicro.py b/dataset_builders/pie/argmicro/argmicro.py index 3ab27c7f..6d4a6c6b 100644 --- a/dataset_builders/pie/argmicro/argmicro.py +++ b/dataset_builders/pie/argmicro/argmicro.py @@ -21,13 +21,8 @@ def dl2ld(dict_of_lists): return [dict(zip(dict_of_lists, t)) for t in zip(*dict_of_lists.values())] -def ld2dl(list_of_dicts, keys: Optional[List[str]] = None, as_list: bool = False): - if keys is None: - keys = list_of_dicts[0].keys() - if as_list: - return [[d[k] for d in list_of_dicts] for k in keys] - else: - return {k: [d[k] for d in list_of_dicts] for k in keys} +def ld2dl(list_of_dicts, keys: Optional[List[str]] = None): + return {k: [d[k] for d in list_of_dicts] for k in keys} @dataclasses.dataclass(frozen=True) @@ -54,11 +49,11 @@ class ArgMicroDocument(TextBasedDocument): def example_to_document( example: Dict[str, Any], - adu_type_int2str: Callable[[int], str], - edge_type_int2str: Callable[[int], str], - stance_int2str: Callable[[int], str], + adu_type_label: datasets.ClassLabel, + edge_type_label: datasets.ClassLabel, + stance_label: datasets.ClassLabel, ) -> ArgMicroDocument: - stance = stance_int2str(example["stance"]) + stance = stance_label.int2str(example["stance"]) document = ArgMicroDocument( id=example["id"], text=example["text"], @@ -73,7 +68,7 @@ def example_to_document( adu_id2edus = defaultdict(list) edges_multi_source = defaultdict(dict) for edge in dl2ld(example["edges"]): - edge_type = edge_type_int2str(edge["type"]) + edge_type = edge_type_label.int2str(edge["type"]) if edge_type == "seg": adu_id2edus[edge["trg"]].append(edus_dict[edge["src"]]) elif edge_type == "add": @@ -88,7 +83,7 @@ def example_to_document( edges_multi_source[edge["id"]]["src"].append(edge["src"]) adus_dict = {} for adu in dl2ld(example["adus"]): - adu_type = adu_type_int2str(adu["type"]) + adu_type = adu_type_label.int2str(adu["type"]) adu_edus = adu_id2edus[adu["id"]] adus_dict[adu["id"]] = LabeledAnnotationCollection( annotations=tuple(adu_edus), label=adu_type @@ -120,27 +115,27 @@ def example_to_document( document.metadata["rel_seg_ids"] = { edge["src"]: edge["id"] for edge in dl2ld(example["edges"]) - if edge_type_int2str(edge["type"]) == "seg" + if edge_type_label.int2str(edge["type"]) == "seg" } document.metadata["rel_add_ids"] = { edge["src"]: edge["id"] for edge in dl2ld(example["edges"]) - if edge_type_int2str(edge["type"]) == "add" + if edge_type_label.int2str(edge["type"]) == "add" } return document def document_to_example( document: ArgMicroDocument, - adu_type_str2int: Callable[[str], int], - edge_type_str2int: Callable[[str], int], - stance_str2int: Callable[[str], int], + adu_type_label: datasets.ClassLabel, + edge_type_label: datasets.ClassLabel, + stance_label: datasets.ClassLabel, ) -> Dict[str, Any]: result = { "id": document.id, "text": document.text, "topic_id": document.topic_id or "UNDEFINED", - "stance": stance_str2int(document.stance or "UNDEFINED"), + "stance": stance_label.str2int(document.stance or "UNDEFINED"), } # construct EDUs @@ -154,7 +149,7 @@ def document_to_example( # construct ADUs adus = { - adu: {"id": adu_id, "type": adu_type_str2int(adu.label)} + adu: {"id": adu_id, "type": adu_type_label.str2int(adu.label)} for adu_id, adu in zip(document.metadata["adu_ids"], document.adus) } result["adus"] = ld2dl(sorted(adus.values(), key=lambda x: x["id"]), keys=["id", "type"]) @@ -180,7 +175,7 @@ def document_to_example( "id": rel_id, "src": source_id, "trg": target_id, - "type": edge_type_str2int(rel.label), + "type": edge_type_label.str2int(rel.label), } edges.append(edge) # if it is an additional support, we need to change the source to the relation that connects the source @@ -191,7 +186,7 @@ def document_to_example( "id": edge_id, "src": source_id, "trg": rel_id, - "type": edge_type_str2int("add"), + "type": edge_type_label.str2int("add"), } edges.append(edge) @@ -204,7 +199,7 @@ def document_to_example( "id": edge_id, "src": source_id, "trg": target_id, - "type": edge_type_str2int("seg"), + "type": edge_type_label.str2int("seg"), } edges.append(edge) @@ -274,15 +269,15 @@ class ArgMicro(GeneratorBasedBuilder): def _generate_document_kwargs(self, dataset): return { - "adu_type_int2str": dataset.features["adus"].feature["type"].int2str, - "edge_type_int2str": dataset.features["edges"].feature["type"].int2str, - "stance_int2str": dataset.features["stance"].int2str, + "adu_type_label": dataset.features["adus"].feature["type"], + "edge_type_label": dataset.features["edges"].feature["type"], + "stance_label": dataset.features["stance"], } - def _generate_document(self, example, adu_type_int2str, edge_type_int2str, stance_int2str): + def _generate_document(self, example, adu_type_label, edge_type_label, stance_label): return example_to_document( example, - adu_type_int2str=adu_type_int2str, - edge_type_int2str=edge_type_int2str, - stance_int2str=stance_int2str, + adu_type_label=adu_type_label, + edge_type_label=edge_type_label, + stance_label=stance_label, ) diff --git a/tests/dataset_builders/pie/test_argmicro.py b/tests/dataset_builders/pie/test_argmicro.py index d1932a83..cc500de6 100644 --- a/tests/dataset_builders/pie/test_argmicro.py +++ b/tests/dataset_builders/pie/test_argmicro.py @@ -44,35 +44,29 @@ def hf_dataset(language): @pytest.fixture(scope="module") -def adu_type_int2str(hf_dataset): +def generate_document_kwargs(hf_dataset, language): ds = hf_dataset["train"] - return ds.features["adus"].feature["type"].int2str + return ArgMicro(config_name=language)._generate_document_kwargs(ds) -@pytest.fixture(scope="module") -def edge_type_int2str(hf_dataset): - ds = hf_dataset["train"] - return ds.features["edges"].feature["type"].int2str - - -@pytest.fixture(scope="module") -def stance_int2str(hf_dataset): - ds = hf_dataset["train"] - return ds.features["stance"].int2str - - -def test_hf_dataset(hf_dataset, language, adu_type_int2str, edge_type_int2str, stance_int2str): +def test_hf_dataset(hf_dataset, language, generate_document_kwargs): assert hf_dataset is not None assert {name: len(ds) for name, ds in hf_dataset.items()} == SPLIT_SIZES ds = hf_dataset["train"] # check topic_id_values = Counter([ex["topic_id"] for ex in ds]) - stance_values = Counter([stance_int2str(ex["stance"]) for ex in ds]) + stance_values = Counter( + [generate_document_kwargs["stance_label"].int2str(ex["stance"]) for ex in ds] + ) adu_type_values = Counter() edge_type_values = Counter() for ex in ds: - adu_type_values.update([adu_type_int2str(t) for t in ex["adus"]["type"]]) - edge_type_values.update([edge_type_int2str(t) for t in ex["edges"]["type"]]) + adu_type_values.update( + [generate_document_kwargs["adu_type_label"].int2str(t) for t in ex["adus"]["type"]] + ) + edge_type_values.update( + [generate_document_kwargs["edge_type_label"].int2str(t) for t in ex["edges"]["type"]] + ) assert dict(topic_id_values) == { "UNDEFINED": 23, "higher_dog_poo_fines": 9, @@ -111,22 +105,24 @@ def hf_example(hf_dataset): return hf_dataset["train"][0] -def test_hf_example( - hf_example, hf_dataset, language, adu_type_int2str, edge_type_int2str, stance_int2str -): +def test_hf_example(hf_example, hf_dataset, language, generate_document_kwargs): fixture_path = HF_DS_FIXTURE_DATA_PATH / DATASET_NAME / f"{language}.train.0.json" # hf_example_expected = json.loads(fixture_path.read_text()) hf_example_expected = json.loads(open(fixture_path, encoding="utf-8").read()) assert hf_example == hf_example_expected - assert stance_int2str(hf_example["stance"]) == "pro" - assert [adu_type_int2str(t) for t in hf_example["adus"]["type"]] == [ + assert generate_document_kwargs["stance_label"].int2str(hf_example["stance"]) == "pro" + assert [ + generate_document_kwargs["adu_type_label"].int2str(t) for t in hf_example["adus"]["type"] + ] == [ "opp", "opp", "pro", "pro", "pro", ] - assert [edge_type_int2str(t) for t in hf_example["edges"]["type"]] == [ + assert [ + generate_document_kwargs["edge_type_label"].int2str(t) for t in hf_example["edges"]["type"] + ] == [ "reb", "seg", "sup", @@ -139,38 +135,46 @@ def test_hf_example( ] -def test_example_to_document( - hf_example, adu_type_int2str, edge_type_int2str, stance_int2str, language -): - doc = example_to_document( - hf_example, - adu_type_int2str=adu_type_int2str, - edge_type_int2str=edge_type_int2str, - stance_int2str=stance_int2str, +# need to find bug +@pytest.fixture(scope="module") +def generated_document(hf_dataset, language, generate_document_kwargs): + return ArgMicro(config_name=language)._generate_document( + hf_dataset["train"][0], **generate_document_kwargs ) - assert doc is not None - assert doc.id == "micro_b001" - assert doc.topic_id == "waste_separation" - assert doc.stance == "pro" - assert len(doc.edus) == 5 - assert doc.metadata["edu_ids"] == ["e1", "e2", "e3", "e4", "e5"] - edus_dict = {edu_id: edu for edu_id, edu in zip(doc.metadata["edu_ids"], doc.edus)} + + +def test_generated_document(generated_document): + assert isinstance(generated_document, ArgMicroDocument) + + +def test_example_to_document(generated_document, language): + assert isinstance(generated_document, ArgMicroDocument) + assert generated_document is not None + assert generated_document.id == "micro_b001" + assert generated_document.topic_id == "waste_separation" + assert generated_document.stance == "pro" + assert len(generated_document.edus) == 5 + assert generated_document.metadata["edu_ids"] == ["e1", "e2", "e3", "e4", "e5"] + edus_dict = { + edu_id: edu + for edu_id, edu in zip(generated_document.metadata["edu_ids"], generated_document.edus) + } if language == "en": assert ( - str(doc.edus[0]) + str(generated_document.edus[0]) == "Yes, it's annoying and cumbersome to separate your rubbish properly all the time." ) assert ( - str(doc.edus[1]) + str(generated_document.edus[1]) == "Three different bin bags stink away in the kitchen and have to be sorted into different wheelie bins." ) - assert str(doc.edus[2]) == "But still Germany produces way too much rubbish" + assert str(generated_document.edus[2]) == "But still Germany produces way too much rubbish" assert ( - str(doc.edus[3]) + str(generated_document.edus[3]) == "and too many resources are lost when what actually should be separated and recycled is burnt." ) assert ( - str(doc.edus[4]) + str(generated_document.edus[4]) == "We Berliners should take the chance and become pioneers in waste separation!" ) elif language == "de": @@ -179,30 +183,38 @@ def test_example_to_document( else: raise ValueError(f"Unknown language {language}") - assert len(doc.adus) == 5 - assert doc.metadata["adu_ids"] == ["a1", "a2", "a3", "a4", "a5"] - adus_dict = {adu_id: adu for adu_id, adu in zip(doc.metadata["adu_ids"], doc.adus)} - assert doc.adus[0].label == "opp" - assert len(doc.adus[0].annotations) == 1 - assert doc.adus[0].annotations[0] == doc.edus[0] - assert doc.adus[1].label == "opp" - assert len(doc.adus[1].annotations) == 1 - assert doc.adus[1].annotations[0] == doc.edus[1] - assert doc.adus[2].label == "pro" - assert len(doc.adus[2].annotations) == 1 - assert doc.adus[2].annotations[0] == doc.edus[2] - assert doc.adus[3].label == "pro" - assert len(doc.adus[3].annotations) == 1 - assert doc.adus[3].annotations[0] == doc.edus[3] - assert doc.adus[4].label == "pro" - assert len(doc.adus[4].annotations) == 1 - assert doc.adus[4].annotations[0] == doc.edus[4] + assert len(generated_document.adus) == 5 + assert generated_document.metadata["adu_ids"] == ["a1", "a2", "a3", "a4", "a5"] + adus_dict = { + adu_id: adu + for adu_id, adu in zip(generated_document.metadata["adu_ids"], generated_document.adus) + } + assert generated_document.adus[0].label == "opp" + assert len(generated_document.adus[0].annotations) == 1 + assert generated_document.adus[0].annotations[0] == generated_document.edus[0] + assert generated_document.adus[1].label == "opp" + assert len(generated_document.adus[1].annotations) == 1 + assert generated_document.adus[1].annotations[0] == generated_document.edus[1] + assert generated_document.adus[2].label == "pro" + assert len(generated_document.adus[2].annotations) == 1 + assert generated_document.adus[2].annotations[0] == generated_document.edus[2] + assert generated_document.adus[3].label == "pro" + assert len(generated_document.adus[3].annotations) == 1 + assert generated_document.adus[3].annotations[0] == generated_document.edus[3] + assert generated_document.adus[4].label == "pro" + assert len(generated_document.adus[4].annotations) == 1 + assert generated_document.adus[4].annotations[0] == generated_document.edus[4] # sources == heads # targets == tails - assert len(doc.relations) == 3 - assert doc.metadata["rel_ids"] == ["c1", "c2", "c3"] - rels_dict = {rel_id: rel for rel_id, rel in zip(doc.metadata["rel_ids"], doc.relations)} + assert len(generated_document.relations) == 3 + assert generated_document.metadata["rel_ids"] == ["c1", "c2", "c3"] + rels_dict = { + rel_id: rel + for rel_id, rel in zip( + generated_document.metadata["rel_ids"], generated_document.relations + ) + } rel = rels_dict["c1"] assert rel.label == "reb" # rebutting attack @@ -226,86 +238,28 @@ def test_example_to_document( assert len(rel.tails) == 1 assert rel.tails[0] == adus_dict["a1"] - assert doc.metadata["rel_seg_ids"] == { + assert generated_document.metadata["rel_seg_ids"] == { "e1": "c6", "e2": "c7", "e3": "c8", "e4": "c9", "e5": "c10", } - assert doc.metadata["rel_add_ids"] == {"a4": "c4"} - - -@pytest.fixture(scope="module") -def adu_type_str2int(hf_dataset): - ds = hf_dataset["train"] - return ds.features["adus"].feature["type"].str2int + assert generated_document.metadata["rel_add_ids"] == {"a4": "c4"} -@pytest.fixture(scope="module") -def edge_type_str2int(hf_dataset): - ds = hf_dataset["train"] - return ds.features["edges"].feature["type"].str2int - - -@pytest.fixture(scope="module") -def stance_str2int(hf_dataset): - ds = hf_dataset["train"] - return ds.features["stance"].str2int - - -def test_example_to_document_and_back( - hf_example, - adu_type_int2str, - edge_type_int2str, - adu_type_str2int, - edge_type_str2int, - stance_int2str, - stance_str2int, -): - doc = example_to_document( - hf_example, - adu_type_int2str=adu_type_int2str, - edge_type_int2str=edge_type_int2str, - stance_int2str=stance_int2str, - ) - hf_example_back = document_to_example( - doc, - adu_type_str2int=adu_type_str2int, - edge_type_str2int=edge_type_str2int, - stance_str2int=stance_str2int, - ) +def test_example_to_document_and_back(hf_example, generated_document, generate_document_kwargs): + hf_example_back = document_to_example(generated_document, **generate_document_kwargs) assert hf_example == hf_example_back -def test_example_to_document_and_back_all( - hf_dataset, - adu_type_int2str, - edge_type_int2str, - adu_type_str2int, - edge_type_str2int, - stance_int2str, - stance_str2int, -): +def test_example_to_document_and_back_all(hf_dataset, generate_document_kwargs): for ex in hf_dataset["train"]: - doc = example_to_document( - ex, - adu_type_int2str=adu_type_int2str, - edge_type_int2str=edge_type_int2str, - stance_int2str=stance_int2str, - ) - ex_back = document_to_example( - doc, - adu_type_str2int=adu_type_str2int, - edge_type_str2int=edge_type_str2int, - stance_str2int=stance_str2int, - ) + doc = example_to_document(ex, **generate_document_kwargs) + ex_back = document_to_example(doc, **generate_document_kwargs) assert ex == ex_back -import datasets - - @pytest.fixture(scope="module") def dataset() -> DatasetDict: return DatasetDict.load_dataset(path=str(PIE_DATASET_PATH), name="en") @@ -326,6 +280,29 @@ def document(dataset) -> ArgMicroDocument: return doc +def test_compare_document_and_generated_document(document, generated_document, language): + if language == "en": + assert document.id == generated_document.id + assert document.topic_id == generated_document.topic_id + assert document.text == generated_document.text + assert document.edus == generated_document.edus + assert ( + document.adus == generated_document.adus + ) # contents seem to be identical, but doesn't work + assert document.stance == generated_document.stance # contents are different: 1 != 'pro' + assert ( + document.relations == generated_document.relations + ) # contents seem to be identical, but doesn't work + assert ( + document.metadata == generated_document.metadata + ) # contents are different; e.g., 'rel_add_ids': {'a4': 'c4'}' != 'rel_add_ids': {'a2': None, 'a3': None, 'a4': 'c4', 'a5': None, 'a6': None}' + elif language == "de": + # we don't check because we only call the dataset in English + pass + else: + raise ValueError(f"Unknown language {language}") + + @pytest.fixture(scope="module") def tokenizer() -> PreTrainedTokenizer: return AutoTokenizer.from_pretrained("bert-base-uncased") From 2083aa97e77a0884f96ffa05e6d89fc42446576b Mon Sep 17 00:00:00 2001 From: Ruangrin L <88072261+idalr@users.noreply.github.com> Date: Tue, 21 Nov 2023 15:25:14 +0100 Subject: [PATCH 04/29] created pie/readme.md --- dataset_builders/pie/argmicro/README.md | 31 +++++++++++++++++++++++++ 1 file changed, 31 insertions(+) create mode 100644 dataset_builders/pie/argmicro/README.md diff --git a/dataset_builders/pie/argmicro/README.md b/dataset_builders/pie/argmicro/README.md new file mode 100644 index 00000000..44f52f5f --- /dev/null +++ b/dataset_builders/pie/argmicro/README.md @@ -0,0 +1,31 @@ +# PIE Dataset Card for "ArgMicro" + +This is a [PyTorch-IE](https://github.com/ChristophAlt/pytorch-ie) wrapper for the +[ArgMicro Huggingface dataset loading script](https://huggingface.co/datasets/DFKI-SLT/argmicro). + +## Data Schema + +The document type for this dataset is `ArgMicroDocument` which defines the following data fields: + +- `id` (str) +- `text` (str) +- `topic_id` (str, optional) +- `stance` (int, optional) +- `metadata` (dictionary, optional) + +and the following annotation layers: + +- `edus` (annotation type: `Span`, target: `text`) +- `adus` (annotation type: `LabeledAnnotationCollection`, target: `edus`) +- `relations` (annotation type: `MultiRelation`, target: `adus`) + +See [here](https://github.com/ChristophAlt/pytorch-ie/blob/main/src/pytorch_ie/annotations.py) for the annotation type definitions. + +## Document Converters + +The dataset provides document converters for the following target document types: + +- `pytorch_ie.documents.TextDocumentWithLabeledSpansAndBinaryRelations` + +See [here](https://github.com/ChristophAlt/pytorch-ie/blob/main/src/pytorch_ie/documents.py) for the document type +definitions. From e0d00dc42c32ee38f8749259e74ffdf58dfb9887 Mon Sep 17 00:00:00 2001 From: Ruangrin L <88072261+idalr@users.noreply.github.com> Date: Tue, 21 Nov 2023 18:02:23 +0100 Subject: [PATCH 05/29] minor fixes --- dataset_builders/pie/argmicro/README.md | 2 +- tests/dataset_builders/pie/test_argmicro.py | 13 +++---------- 2 files changed, 4 insertions(+), 11 deletions(-) diff --git a/dataset_builders/pie/argmicro/README.md b/dataset_builders/pie/argmicro/README.md index 44f52f5f..2b802437 100644 --- a/dataset_builders/pie/argmicro/README.md +++ b/dataset_builders/pie/argmicro/README.md @@ -10,7 +10,7 @@ The document type for this dataset is `ArgMicroDocument` which defines the follo - `id` (str) - `text` (str) - `topic_id` (str, optional) -- `stance` (int, optional) +- `stance` (str, optional) - `metadata` (dictionary, optional) and the following annotation layers: diff --git a/tests/dataset_builders/pie/test_argmicro.py b/tests/dataset_builders/pie/test_argmicro.py index cc500de6..547c547c 100644 --- a/tests/dataset_builders/pie/test_argmicro.py +++ b/tests/dataset_builders/pie/test_argmicro.py @@ -143,10 +143,6 @@ def generated_document(hf_dataset, language, generate_document_kwargs): ) -def test_generated_document(generated_document): - assert isinstance(generated_document, ArgMicroDocument) - - def test_example_to_document(generated_document, language): assert isinstance(generated_document, ArgMicroDocument) assert generated_document is not None @@ -282,17 +278,14 @@ def document(dataset) -> ArgMicroDocument: def test_compare_document_and_generated_document(document, generated_document, language): if language == "en": + document = document.as_type(type(generated_document)) assert document.id == generated_document.id assert document.topic_id == generated_document.topic_id assert document.text == generated_document.text assert document.edus == generated_document.edus - assert ( - document.adus == generated_document.adus - ) # contents seem to be identical, but doesn't work + assert document.adus == generated_document.adus assert document.stance == generated_document.stance # contents are different: 1 != 'pro' - assert ( - document.relations == generated_document.relations - ) # contents seem to be identical, but doesn't work + assert document.relations == generated_document.relations assert ( document.metadata == generated_document.metadata ) # contents are different; e.g., 'rel_add_ids': {'a4': 'c4'}' != 'rel_add_ids': {'a2': None, 'a3': None, 'a4': 'c4', 'a5': None, 'a6': None}' From 243500fc94f7ba30cbb064f288816ac6202eb018 Mon Sep 17 00:00:00 2001 From: Arne Binder Date: Tue, 21 Nov 2023 18:32:10 +0100 Subject: [PATCH 06/29] make stance an annotation layer of Label and fix tests --- dataset_builders/pie/argmicro/argmicro.py | 28 +++++++------- tests/dataset_builders/pie/test_argmicro.py | 41 +++++++++++++++------ 2 files changed, 44 insertions(+), 25 deletions(-) diff --git a/dataset_builders/pie/argmicro/argmicro.py b/dataset_builders/pie/argmicro/argmicro.py index 6d4a6c6b..5bc2da26 100644 --- a/dataset_builders/pie/argmicro/argmicro.py +++ b/dataset_builders/pie/argmicro/argmicro.py @@ -1,11 +1,12 @@ +import copy import dataclasses import logging from collections import defaultdict from itertools import combinations -from typing import Any, Callable, Dict, List, Optional, Set, Tuple +from typing import Any, Dict, List, Optional, Set, Tuple import datasets -from pytorch_ie.annotations import BinaryRelation, LabeledSpan, Span +from pytorch_ie.annotations import BinaryRelation, Label, LabeledSpan, Span from pytorch_ie.core import Annotation, AnnotationList, annotation_field from pytorch_ie.documents import ( TextBasedDocument, @@ -41,7 +42,7 @@ class MultiRelation(Annotation): @dataclasses.dataclass class ArgMicroDocument(TextBasedDocument): topic_id: Optional[str] = None - stance: Optional[str] = None + stance: AnnotationList[Label] = annotation_field() edus: AnnotationList[Span] = annotation_field(target="text") adus: AnnotationList[LabeledAnnotationCollection] = annotation_field(target="edus") relations: AnnotationList[MultiRelation] = annotation_field(target="adus") @@ -58,8 +59,10 @@ def example_to_document( id=example["id"], text=example["text"], topic_id=example["topic_id"] if example["topic_id"] != "UNDEFINED" else None, - stance=stance if stance != "UNDEFINED" else None, ) + if stance != "UNDEFINED": + document.stance.append(Label(label=stance)) + # build EDUs edus_dict = { edu["id"]: Span(start=edu["start"], end=edu["end"]) for edu in dl2ld(example["edus"]) @@ -131,11 +134,12 @@ def document_to_example( edge_type_label: datasets.ClassLabel, stance_label: datasets.ClassLabel, ) -> Dict[str, Any]: + stance = document.stance[0].label if len(document.stance) else "UNDEFINED" result = { "id": document.id, "text": document.text, "topic_id": document.topic_id or "UNDEFINED", - "stance": stance_label.str2int(document.stance or "UNDEFINED"), + "stance": stance_label.str2int(stance), } # construct EDUs @@ -243,8 +247,9 @@ def convert_to_text_document_with_labeled_spans_and_binary_relations( rel = BinaryRelation(label="joint", head=adu2entity[head2], tail=adu2entity[head1]) relations.append(rel) - metadata = dict(doc.metadata) - metadata["stance"] = doc.stance + metadata = copy.deepcopy(doc.metadata) + if len(doc.stance) > 0: + metadata["stance"] = doc.stance[0].label metadata["topic"] = doc.topic_id result = TextDocumentWithLabeledSpansAndBinaryRelations( text=doc.text, id=doc.id, metadata=doc.metadata @@ -274,10 +279,5 @@ def _generate_document_kwargs(self, dataset): "stance_label": dataset.features["stance"], } - def _generate_document(self, example, adu_type_label, edge_type_label, stance_label): - return example_to_document( - example, - adu_type_label=adu_type_label, - edge_type_label=edge_type_label, - stance_label=stance_label, - ) + def _generate_document(self, example, **kwargs): + return example_to_document(example, **kwargs) diff --git a/tests/dataset_builders/pie/test_argmicro.py b/tests/dataset_builders/pie/test_argmicro.py index 547c547c..36772744 100644 --- a/tests/dataset_builders/pie/test_argmicro.py +++ b/tests/dataset_builders/pie/test_argmicro.py @@ -143,12 +143,16 @@ def generated_document(hf_dataset, language, generate_document_kwargs): ) +def test_generated_document(generated_document): + assert isinstance(generated_document, ArgMicroDocument) + + def test_example_to_document(generated_document, language): assert isinstance(generated_document, ArgMicroDocument) assert generated_document is not None assert generated_document.id == "micro_b001" assert generated_document.topic_id == "waste_separation" - assert generated_document.stance == "pro" + assert generated_document.stance[0].label == "pro" assert len(generated_document.edus) == 5 assert generated_document.metadata["edu_ids"] == ["e1", "e2", "e3", "e4", "e5"] edus_dict = { @@ -277,18 +281,33 @@ def document(dataset) -> ArgMicroDocument: def test_compare_document_and_generated_document(document, generated_document, language): + casted_document = document.as_type(type(generated_document)) if language == "en": - document = document.as_type(type(generated_document)) - assert document.id == generated_document.id - assert document.topic_id == generated_document.topic_id - assert document.text == generated_document.text - assert document.edus == generated_document.edus - assert document.adus == generated_document.adus - assert document.stance == generated_document.stance # contents are different: 1 != 'pro' - assert document.relations == generated_document.relations + assert casted_document.id == generated_document.id + assert casted_document.topic_id == generated_document.topic_id + assert casted_document.text == generated_document.text + assert casted_document.edus == generated_document.edus + assert ( + casted_document.adus == generated_document.adus + ) # contents seem to be identical, but doesn't work + assert ( + casted_document.stance == generated_document.stance + ) # contents are different: 1 != 'pro' assert ( - document.metadata == generated_document.metadata - ) # contents are different; e.g., 'rel_add_ids': {'a4': 'c4'}' != 'rel_add_ids': {'a2': None, 'a3': None, 'a4': 'c4', 'a5': None, 'a6': None}' + casted_document.relations == generated_document.relations + ) # contents seem to be identical, but doesn't work + + # contents of metadata are different: there are additional keys with None values + # e.g., 'rel_add_ids': {'a4': 'c4'}' != 'rel_add_ids': {'a2': None, 'a3': None, 'a4': 'c4', 'a5': None, 'a6': None}' + # it looks like Huggingface datasets creates a kind of schema from the data and adds all keys it finds + for k in set(generated_document.metadata) | set(casted_document.metadata): + v = generated_document.metadata[k] + v_expected = casted_document.metadata[k] + if isinstance(v, dict): + v_expected_without_none = {k: v for k, v in v_expected.items() if v is not None} + assert v == v_expected_without_none + else: + assert v == v_expected elif language == "de": # we don't check because we only call the dataset in English pass From fd315e5f463631afa657ab20d24980604f1f48bd Mon Sep 17 00:00:00 2001 From: Arne Binder Date: Tue, 21 Nov 2023 18:55:34 +0100 Subject: [PATCH 07/29] minor fix --- tests/dataset_builders/pie/test_argmicro.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/dataset_builders/pie/test_argmicro.py b/tests/dataset_builders/pie/test_argmicro.py index 36772744..ef751ee1 100644 --- a/tests/dataset_builders/pie/test_argmicro.py +++ b/tests/dataset_builders/pie/test_argmicro.py @@ -297,8 +297,8 @@ def test_compare_document_and_generated_document(document, generated_document, l casted_document.relations == generated_document.relations ) # contents seem to be identical, but doesn't work - # contents of metadata are different: there are additional keys with None values - # e.g., 'rel_add_ids': {'a4': 'c4'}' != 'rel_add_ids': {'a2': None, 'a3': None, 'a4': 'c4', 'a5': None, 'a6': None}' + # contents of metadata are different: there are additional keys with None values e.g., + # 'rel_add_ids': {'a4': 'c4'}' != 'rel_add_ids': {'a2': None, 'a3': None, 'a4': 'c4', 'a5': None, 'a6': None}' # it looks like Huggingface datasets creates a kind of schema from the data and adds all keys it finds for k in set(generated_document.metadata) | set(casted_document.metadata): v = generated_document.metadata[k] From 2a2be5f4cff9b6da9fcc005609813ef6369f7c92 Mon Sep 17 00:00:00 2001 From: Arne Binder Date: Tue, 21 Nov 2023 19:13:35 +0100 Subject: [PATCH 08/29] cleanup --- tests/dataset_builders/pie/test_argmicro.py | 17 +++++++---------- 1 file changed, 7 insertions(+), 10 deletions(-) diff --git a/tests/dataset_builders/pie/test_argmicro.py b/tests/dataset_builders/pie/test_argmicro.py index ef751ee1..bd70cdc9 100644 --- a/tests/dataset_builders/pie/test_argmicro.py +++ b/tests/dataset_builders/pie/test_argmicro.py @@ -281,22 +281,19 @@ def document(dataset) -> ArgMicroDocument: def test_compare_document_and_generated_document(document, generated_document, language): + # We cast the document to the type of the generated document to compare them. + # This is necessary because the document may come from a dataset loading script + # downloaded to a temporary directory and thus have a different type object, although it is + # semantically the same. casted_document = document.as_type(type(generated_document)) if language == "en": assert casted_document.id == generated_document.id assert casted_document.topic_id == generated_document.topic_id assert casted_document.text == generated_document.text assert casted_document.edus == generated_document.edus - assert ( - casted_document.adus == generated_document.adus - ) # contents seem to be identical, but doesn't work - assert ( - casted_document.stance == generated_document.stance - ) # contents are different: 1 != 'pro' - assert ( - casted_document.relations == generated_document.relations - ) # contents seem to be identical, but doesn't work - + assert casted_document.adus == generated_document.adus + assert casted_document.stance == generated_document.stance + assert casted_document.relations == generated_document.relations # contents of metadata are different: there are additional keys with None values e.g., # 'rel_add_ids': {'a4': 'c4'}' != 'rel_add_ids': {'a2': None, 'a3': None, 'a4': 'c4', 'a5': None, 'a6': None}' # it looks like Huggingface datasets creates a kind of schema from the data and adds all keys it finds From d5e3d6c99808f8b4975cebacaf4ecb8081098f01 Mon Sep 17 00:00:00 2001 From: Arne Binder Date: Tue, 21 Nov 2023 19:15:24 +0100 Subject: [PATCH 09/29] cleanup --- tests/dataset_builders/pie/test_argmicro.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/tests/dataset_builders/pie/test_argmicro.py b/tests/dataset_builders/pie/test_argmicro.py index bd70cdc9..ab328984 100644 --- a/tests/dataset_builders/pie/test_argmicro.py +++ b/tests/dataset_builders/pie/test_argmicro.py @@ -298,11 +298,11 @@ def test_compare_document_and_generated_document(document, generated_document, l # 'rel_add_ids': {'a4': 'c4'}' != 'rel_add_ids': {'a2': None, 'a3': None, 'a4': 'c4', 'a5': None, 'a6': None}' # it looks like Huggingface datasets creates a kind of schema from the data and adds all keys it finds for k in set(generated_document.metadata) | set(casted_document.metadata): - v = generated_document.metadata[k] - v_expected = casted_document.metadata[k] + v_expected = generated_document.metadata[k] + v = casted_document.metadata[k] if isinstance(v, dict): - v_expected_without_none = {k: v for k, v in v_expected.items() if v is not None} - assert v == v_expected_without_none + v_without_none = {k: v for k, v in v.items() if v is not None} + assert v_without_none == v_expected else: assert v == v_expected elif language == "de": From 41aed4831b4cf88e5d86d56b812e7d909c0cab34 Mon Sep 17 00:00:00 2001 From: Arne Binder Date: Wed, 22 Nov 2023 23:44:13 +0100 Subject: [PATCH 10/29] fix and cleanup imports --- tests/dataset_builders/pie/test_argmicro.py | 7 ++----- 1 file changed, 2 insertions(+), 5 deletions(-) diff --git a/tests/dataset_builders/pie/test_argmicro.py b/tests/dataset_builders/pie/test_argmicro.py index ab328984..63126616 100644 --- a/tests/dataset_builders/pie/test_argmicro.py +++ b/tests/dataset_builders/pie/test_argmicro.py @@ -5,10 +5,7 @@ import pytest from datasets import disable_caching, load_dataset from pytorch_ie.core import Document -from pytorch_ie.documents import ( - TextBasedDocument, - TextDocumentWithLabeledSpansAndBinaryRelations, -) +from pytorch_ie.documents import TextDocumentWithLabeledSpansAndBinaryRelations from transformers import AutoTokenizer, PreTrainedTokenizer from dataset_builders.pie.argmicro.argmicro import ( @@ -19,7 +16,7 @@ example_to_document, ) from pie_datasets import DatasetDict -from pie_datasets.document.conversion import tokenize_document +from pie_datasets.document.processing import tokenize_document from pie_datasets.document.types import TokenDocumentWithLabeledSpansAndBinaryRelations from tests import FIXTURES_ROOT from tests.dataset_builders.common import HF_DS_FIXTURE_DATA_PATH, PIE_BASE_PATH From 926933f057f2f750ea6db2c9997aab6bedf5c21e Mon Sep 17 00:00:00 2001 From: Arne Binder Date: Thu, 23 Nov 2023 10:31:29 +0100 Subject: [PATCH 11/29] set max version for pie-datasets --- dataset_builders/pie/argmicro/requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/dataset_builders/pie/argmicro/requirements.txt b/dataset_builders/pie/argmicro/requirements.txt index 738010cb..2c289fa6 100644 --- a/dataset_builders/pie/argmicro/requirements.txt +++ b/dataset_builders/pie/argmicro/requirements.txt @@ -1 +1 @@ -pie-datasets>=0.3.3 +pie-datasets>=0.3.3,<0.5.0 From df93495841fcc473813f0a228f9685db2acf9c68 Mon Sep 17 00:00:00 2001 From: Ruangrin L <88072261+idalr@users.noreply.github.com> Date: Thu, 23 Nov 2023 13:50:33 +0100 Subject: [PATCH 12/29] rename fixture to `dataset_variant` and minor fix --- tests/dataset_builders/pie/test_argmicro.py | 40 ++++++++++----------- 1 file changed, 19 insertions(+), 21 deletions(-) diff --git a/tests/dataset_builders/pie/test_argmicro.py b/tests/dataset_builders/pie/test_argmicro.py index 63126616..337f51e3 100644 --- a/tests/dataset_builders/pie/test_argmicro.py +++ b/tests/dataset_builders/pie/test_argmicro.py @@ -30,27 +30,26 @@ PIE_DATASET_PATH = PIE_BASE_PATH / DATASET_NAME -@pytest.fixture(scope="module", params=["en", "de"]) -def language(request): +@pytest.fixture(scope="module", params=[config.name for config in ArgMicro.BUILDER_CONFIGS]) +def dataset_variant(request): return request.param @pytest.fixture(scope="module") -def hf_dataset(language): - return load_dataset(str(HF_DATASET_PATH), name=language, data_dir=DATA_PATH) +def hf_dataset(dataset_variant): + return load_dataset(str(HF_DATASET_PATH), name=dataset_variant, data_dir=DATA_PATH) @pytest.fixture(scope="module") -def generate_document_kwargs(hf_dataset, language): +def generate_document_kwargs(hf_dataset, dataset_variant): ds = hf_dataset["train"] - return ArgMicro(config_name=language)._generate_document_kwargs(ds) + return ArgMicro(config_name=dataset_variant)._generate_document_kwargs(ds) -def test_hf_dataset(hf_dataset, language, generate_document_kwargs): +def test_hf_dataset(hf_dataset, dataset_variant, generate_document_kwargs): assert hf_dataset is not None assert {name: len(ds) for name, ds in hf_dataset.items()} == SPLIT_SIZES ds = hf_dataset["train"] - # check topic_id_values = Counter([ex["topic_id"] for ex in ds]) stance_values = Counter( [generate_document_kwargs["stance_label"].int2str(ex["stance"]) for ex in ds] @@ -102,8 +101,8 @@ def hf_example(hf_dataset): return hf_dataset["train"][0] -def test_hf_example(hf_example, hf_dataset, language, generate_document_kwargs): - fixture_path = HF_DS_FIXTURE_DATA_PATH / DATASET_NAME / f"{language}.train.0.json" +def test_hf_example(hf_example, hf_dataset, dataset_variant, generate_document_kwargs): + fixture_path = HF_DS_FIXTURE_DATA_PATH / DATASET_NAME / f"{dataset_variant}.train.0.json" # hf_example_expected = json.loads(fixture_path.read_text()) hf_example_expected = json.loads(open(fixture_path, encoding="utf-8").read()) assert hf_example == hf_example_expected @@ -132,10 +131,9 @@ def test_hf_example(hf_example, hf_dataset, language, generate_document_kwargs): ] -# need to find bug @pytest.fixture(scope="module") -def generated_document(hf_dataset, language, generate_document_kwargs): - return ArgMicro(config_name=language)._generate_document( +def generated_document(hf_dataset, dataset_variant, generate_document_kwargs): + return ArgMicro(config_name=dataset_variant)._generate_document( hf_dataset["train"][0], **generate_document_kwargs ) @@ -144,7 +142,7 @@ def test_generated_document(generated_document): assert isinstance(generated_document, ArgMicroDocument) -def test_example_to_document(generated_document, language): +def test_example_to_document(generated_document, dataset_variant): assert isinstance(generated_document, ArgMicroDocument) assert generated_document is not None assert generated_document.id == "micro_b001" @@ -156,7 +154,7 @@ def test_example_to_document(generated_document, language): edu_id: edu for edu_id, edu in zip(generated_document.metadata["edu_ids"], generated_document.edus) } - if language == "en": + if dataset_variant == "en": assert ( str(generated_document.edus[0]) == "Yes, it's annoying and cumbersome to separate your rubbish properly all the time." @@ -174,11 +172,11 @@ def test_example_to_document(generated_document, language): str(generated_document.edus[4]) == "We Berliners should take the chance and become pioneers in waste separation!" ) - elif language == "de": + elif dataset_variant == "de": # we don't check this because spellcheck would complain pass else: - raise ValueError(f"Unknown language {language}") + raise ValueError(f"Unknown dataset variant {dataset_variant}") assert len(generated_document.adus) == 5 assert generated_document.metadata["adu_ids"] == ["a1", "a2", "a3", "a4", "a5"] @@ -277,13 +275,13 @@ def document(dataset) -> ArgMicroDocument: return doc -def test_compare_document_and_generated_document(document, generated_document, language): +def test_compare_document_and_generated_document(document, generated_document, dataset_variant): # We cast the document to the type of the generated document to compare them. # This is necessary because the document may come from a dataset loading script # downloaded to a temporary directory and thus have a different type object, although it is # semantically the same. casted_document = document.as_type(type(generated_document)) - if language == "en": + if dataset_variant == "en": assert casted_document.id == generated_document.id assert casted_document.topic_id == generated_document.topic_id assert casted_document.text == generated_document.text @@ -302,11 +300,11 @@ def test_compare_document_and_generated_document(document, generated_document, l assert v_without_none == v_expected else: assert v == v_expected - elif language == "de": + elif dataset_variant == "de": # we don't check because we only call the dataset in English pass else: - raise ValueError(f"Unknown language {language}") + raise ValueError(f"Unknown dataset_variant {dataset_variant}") @pytest.fixture(scope="module") From a535dff612234e03acda1ff305433511ae679287 Mon Sep 17 00:00:00 2001 From: Ruangrin L <88072261+idalr@users.noreply.github.com> Date: Thu, 23 Nov 2023 17:25:13 +0100 Subject: [PATCH 13/29] edit pie/readme.md and minor fix --- dataset_builders/pie/argmicro/README.md | 24 +++++++++++++++++++-- tests/dataset_builders/pie/test_argmicro.py | 3 +-- 2 files changed, 23 insertions(+), 4 deletions(-) diff --git a/dataset_builders/pie/argmicro/README.md b/dataset_builders/pie/argmicro/README.md index 2b802437..33cd8837 100644 --- a/dataset_builders/pie/argmicro/README.md +++ b/dataset_builders/pie/argmicro/README.md @@ -3,6 +3,13 @@ This is a [PyTorch-IE](https://github.com/ChristophAlt/pytorch-ie) wrapper for the [ArgMicro Huggingface dataset loading script](https://huggingface.co/datasets/DFKI-SLT/argmicro). +## Dataset Variants + +The dataset contains two `BuilderConfig`'s: + +- `de`: with the original texts collection in German +- `en`: with the English-translated texts + ## Data Schema The document type for this dataset is `ArgMicroDocument` which defines the following data fields: @@ -10,22 +17,35 @@ The document type for this dataset is `ArgMicroDocument` which defines the follo - `id` (str) - `text` (str) - `topic_id` (str, optional) -- `stance` (str, optional) - `metadata` (dictionary, optional) and the following annotation layers: +- `stance` (annotation type: `Label`) - `edus` (annotation type: `Span`, target: `text`) -- `adus` (annotation type: `LabeledAnnotationCollection`, target: `edus`) +- `adus` (tuple, annotation type: `LabeledAnnotationCollection`, target: `edus`) + - `annotations` (annotation type: `Span`, target: `text`) + - `label` (str, optional) - `relations` (annotation type: `MultiRelation`, target: `adus`) + - `head` (tuple, annotation type: `LabeledAnnotationCollection`, target: `adus`) + - `tail` (tuple, annotation type: `LabeledAnnotationCollection`, target: `adus`) + - `label` (str, optional) See [here](https://github.com/ChristophAlt/pytorch-ie/blob/main/src/pytorch_ie/annotations.py) for the annotation type definitions. +In addition to common annotation type definitions above, `ArgMicroDocument` contains special annotation types: `LabeledAnnotationCollection` and `MultiRelation`. +Both of which contain a tuple of one `Annotation` or more, as the document allows an `adus` with multiple `Span`'s, as well as a relation with multiple `head`'s and/or `tail`'s. + ## Document Converters The dataset provides document converters for the following target document types: - `pytorch_ie.documents.TextDocumentWithLabeledSpansAndBinaryRelations` + - `LabeledSpans`, converted from `ArgMicroDocument`'s `adus` + - if `adus` contains multiple spans, we take the start of the first `edu` and the end of the last `edu` as the boundaries of `LabeledSpan`. We also raise exceptions when there is an overlapping. + - `BinraryRelations`, converted from `ArgMicroDocument`'s `relations` + - if `relations` contains multiple `adus` as `head` and/or `tail`, then we build `BinaryRelations` between each `head`/`tail` to the other component. Then, we build `BinaryRelations` between each component that previously belongs to the same `LabeledAnnotationCollection`. + - `metadata`, we keep the `stance`, `topic_id`, and the rest of `ArgMicroDocument`'s `metadata`. See [here](https://github.com/ChristophAlt/pytorch-ie/blob/main/src/pytorch_ie/documents.py) for the document type definitions. diff --git a/tests/dataset_builders/pie/test_argmicro.py b/tests/dataset_builders/pie/test_argmicro.py index 337f51e3..e81fece3 100644 --- a/tests/dataset_builders/pie/test_argmicro.py +++ b/tests/dataset_builders/pie/test_argmicro.py @@ -103,8 +103,7 @@ def hf_example(hf_dataset): def test_hf_example(hf_example, hf_dataset, dataset_variant, generate_document_kwargs): fixture_path = HF_DS_FIXTURE_DATA_PATH / DATASET_NAME / f"{dataset_variant}.train.0.json" - # hf_example_expected = json.loads(fixture_path.read_text()) - hf_example_expected = json.loads(open(fixture_path, encoding="utf-8").read()) + hf_example_expected = json.load(open(fixture_path, encoding="utf-8")) assert hf_example == hf_example_expected assert generate_document_kwargs["stance_label"].int2str(hf_example["stance"]) == "pro" assert [ From 588dcf75136946953a2928921ed308fab2dfc289 Mon Sep 17 00:00:00 2001 From: Arne Binder Date: Fri, 24 Nov 2023 19:41:54 +0100 Subject: [PATCH 14/29] re-arrange and add TODOs --- dataset_builders/pie/argmicro/README.md | 23 ++++++++++++----------- 1 file changed, 12 insertions(+), 11 deletions(-) diff --git a/dataset_builders/pie/argmicro/README.md b/dataset_builders/pie/argmicro/README.md index 33cd8837..6f0063db 100644 --- a/dataset_builders/pie/argmicro/README.md +++ b/dataset_builders/pie/argmicro/README.md @@ -24,27 +24,28 @@ and the following annotation layers: - `stance` (annotation type: `Label`) - `edus` (annotation type: `Span`, target: `text`) - `adus` (tuple, annotation type: `LabeledAnnotationCollection`, target: `edus`) - - `annotations` (annotation type: `Span`, target: `text`) - - `label` (str, optional) + - description: TODO (*why* do we need to have this special annotation type? i.e. why `adus` with multiple `Span`?) + - `LabeledAnnotationCollection` has the following fields: + - `annotations` (annotation type: `Span`, target: `text`) + - `label` (str, optional), values: TODO - `relations` (annotation type: `MultiRelation`, target: `adus`) - - `head` (tuple, annotation type: `LabeledAnnotationCollection`, target: `adus`) - - `tail` (tuple, annotation type: `LabeledAnnotationCollection`, target: `adus`) - - `label` (str, optional) + - description: TODO (*why* do we need to have this special annotation type? i.e. why relations with multiple `head`'s and/or `tail`'s?) + - `MultiRelation` has the following fields: + - `head` (tuple, annotation type: `LabeledAnnotationCollection`, target: `adus`) + - `tail` (tuple, annotation type: `LabeledAnnotationCollection`, target: `adus`) + - `label` (str, optional), values: TODO See [here](https://github.com/ChristophAlt/pytorch-ie/blob/main/src/pytorch_ie/annotations.py) for the annotation type definitions. -In addition to common annotation type definitions above, `ArgMicroDocument` contains special annotation types: `LabeledAnnotationCollection` and `MultiRelation`. -Both of which contain a tuple of one `Annotation` or more, as the document allows an `adus` with multiple `Span`'s, as well as a relation with multiple `head`'s and/or `tail`'s. - ## Document Converters The dataset provides document converters for the following target document types: - `pytorch_ie.documents.TextDocumentWithLabeledSpansAndBinaryRelations` - - `LabeledSpans`, converted from `ArgMicroDocument`'s `adus` + - `LabeledSpans`, converted from `ArgMicroDocument`'s `adus`, labels: TODO - if `adus` contains multiple spans, we take the start of the first `edu` and the end of the last `edu` as the boundaries of `LabeledSpan`. We also raise exceptions when there is an overlapping. - - `BinraryRelations`, converted from `ArgMicroDocument`'s `relations` - - if `relations` contains multiple `adus` as `head` and/or `tail`, then we build `BinaryRelations` between each `head`/`tail` to the other component. Then, we build `BinaryRelations` between each component that previously belongs to the same `LabeledAnnotationCollection`. + - `BinraryRelations`, converted from `ArgMicroDocument`'s `relations`, labels: TODO + - if `relations` contains multiple `adus` as `head` and/or `tail`, then we build `BinaryRelations` between each `head`/`tail` to the other component (TODO: with which label?). Then, we build `BinaryRelations` between each component that previously belongs to the same `LabeledAnnotationCollection` (TODO: with which label?). - `metadata`, we keep the `stance`, `topic_id`, and the rest of `ArgMicroDocument`'s `metadata`. See [here](https://github.com/ChristophAlt/pytorch-ie/blob/main/src/pytorch_ie/documents.py) for the document type From 9e5da9b328478496b548f1f06862308335413a8d Mon Sep 17 00:00:00 2001 From: Arne Binder Date: Sun, 26 Nov 2023 07:23:46 +0100 Subject: [PATCH 15/29] adjust for 0.5.0 --- dataset_builders/pie/argmicro/requirements.txt | 2 +- tests/dataset_builders/pie/test_argmicro.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/dataset_builders/pie/argmicro/requirements.txt b/dataset_builders/pie/argmicro/requirements.txt index 2c289fa6..6e799260 100644 --- a/dataset_builders/pie/argmicro/requirements.txt +++ b/dataset_builders/pie/argmicro/requirements.txt @@ -1 +1 @@ -pie-datasets>=0.3.3,<0.5.0 +pie-datasets>=0.3.3,<0.6.0 diff --git a/tests/dataset_builders/pie/test_argmicro.py b/tests/dataset_builders/pie/test_argmicro.py index e81fece3..3a13c5f5 100644 --- a/tests/dataset_builders/pie/test_argmicro.py +++ b/tests/dataset_builders/pie/test_argmicro.py @@ -4,6 +4,7 @@ import pytest from datasets import disable_caching, load_dataset +from pie_models.document.processing import tokenize_document from pytorch_ie.core import Document from pytorch_ie.documents import TextDocumentWithLabeledSpansAndBinaryRelations from transformers import AutoTokenizer, PreTrainedTokenizer @@ -16,7 +17,6 @@ example_to_document, ) from pie_datasets import DatasetDict -from pie_datasets.document.processing import tokenize_document from pie_datasets.document.types import TokenDocumentWithLabeledSpansAndBinaryRelations from tests import FIXTURES_ROOT from tests.dataset_builders.common import HF_DS_FIXTURE_DATA_PATH, PIE_BASE_PATH From e1f273d88bf91c26c4ede8a2ebc4023c0e99cb7e Mon Sep 17 00:00:00 2001 From: Arne Binder Date: Sun, 26 Nov 2023 21:35:48 +0100 Subject: [PATCH 16/29] adjust for pie-modules --- dataset_builders/pie/argmicro/requirements.txt | 2 +- tests/dataset_builders/pie/test_argmicro.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/dataset_builders/pie/argmicro/requirements.txt b/dataset_builders/pie/argmicro/requirements.txt index 6e799260..f22877a0 100644 --- a/dataset_builders/pie/argmicro/requirements.txt +++ b/dataset_builders/pie/argmicro/requirements.txt @@ -1 +1 @@ -pie-datasets>=0.3.3,<0.6.0 +pie-datasets>=0.3.3,<0.7.0 diff --git a/tests/dataset_builders/pie/test_argmicro.py b/tests/dataset_builders/pie/test_argmicro.py index 3a13c5f5..d2be9cc3 100644 --- a/tests/dataset_builders/pie/test_argmicro.py +++ b/tests/dataset_builders/pie/test_argmicro.py @@ -4,7 +4,7 @@ import pytest from datasets import disable_caching, load_dataset -from pie_models.document.processing import tokenize_document +from pie_modules.document.processing import tokenize_document from pytorch_ie.core import Document from pytorch_ie.documents import TextDocumentWithLabeledSpansAndBinaryRelations from transformers import AutoTokenizer, PreTrainedTokenizer From aa39e2c733949fc55bf809fb031aaa848e8a8f1e Mon Sep 17 00:00:00 2001 From: Arne Binder Date: Mon, 27 Nov 2023 12:09:05 +0100 Subject: [PATCH 17/29] use test document types --- tests/dataset_builders/pie/test_argmicro.py | 13 ++++++++----- 1 file changed, 8 insertions(+), 5 deletions(-) diff --git a/tests/dataset_builders/pie/test_argmicro.py b/tests/dataset_builders/pie/test_argmicro.py index d2be9cc3..8abdecc6 100644 --- a/tests/dataset_builders/pie/test_argmicro.py +++ b/tests/dataset_builders/pie/test_argmicro.py @@ -17,9 +17,12 @@ example_to_document, ) from pie_datasets import DatasetDict -from pie_datasets.document.types import TokenDocumentWithLabeledSpansAndBinaryRelations from tests import FIXTURES_ROOT -from tests.dataset_builders.common import HF_DS_FIXTURE_DATA_PATH, PIE_BASE_PATH +from tests.dataset_builders.common import ( + HF_DS_FIXTURE_DATA_PATH, + PIE_BASE_PATH, + TestTokenDocumentWithLabeledSpansAndBinaryRelations, +) disable_caching() @@ -403,7 +406,7 @@ def test_dataset_of_text_documents_with_labeled_spans_and_binary_relations( @pytest.fixture(scope="module") def tokenized_documents_with_labeled_spans_and_binary_relations( dataset_of_text_documents_with_labeled_spans_and_binary_relations, tokenizer -) -> List[TokenDocumentWithLabeledSpansAndBinaryRelations]: +) -> List[TestTokenDocumentWithLabeledSpansAndBinaryRelations]: # get a document to check doc = dataset_of_text_documents_with_labeled_spans_and_binary_relations["train"][0] # Note, that this is a list of documents, because the document may be split into chunks @@ -412,7 +415,7 @@ def tokenized_documents_with_labeled_spans_and_binary_relations( doc, tokenizer=tokenizer, return_overflowing_tokens=True, - result_document_type=TokenDocumentWithLabeledSpansAndBinaryRelations, + result_document_type=TestTokenDocumentWithLabeledSpansAndBinaryRelations, verbose=True, ) return tokenized_docs @@ -535,7 +538,7 @@ def test_tokenized_documents_with_entities_and_relations_all( doc, tokenizer=tokenizer, return_overflowing_tokens=True, - result_document_type=TokenDocumentWithLabeledSpansAndBinaryRelations, + result_document_type=TestTokenDocumentWithLabeledSpansAndBinaryRelations, verbose=True, ) # we just ensure that we get at least one tokenized document From 2a9c40a8fe7c829167b37dad284821c8bb3e5fbe Mon Sep 17 00:00:00 2001 From: Ruangrin L <88072261+idalr@users.noreply.github.com> Date: Thu, 30 Nov 2023 17:12:20 +0100 Subject: [PATCH 18/29] edit pie/readme.md --- dataset_builders/pie/argmicro/README.md | 18 ++++++++++-------- 1 file changed, 10 insertions(+), 8 deletions(-) diff --git a/dataset_builders/pie/argmicro/README.md b/dataset_builders/pie/argmicro/README.md index 6f0063db..be6d571a 100644 --- a/dataset_builders/pie/argmicro/README.md +++ b/dataset_builders/pie/argmicro/README.md @@ -21,19 +21,19 @@ The document type for this dataset is `ArgMicroDocument` which defines the follo and the following annotation layers: -- `stance` (annotation type: `Label`) +- `stance` (annotation type: `Label`, see [here](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L35)) - `edus` (annotation type: `Span`, target: `text`) - `adus` (tuple, annotation type: `LabeledAnnotationCollection`, target: `edus`) - - description: TODO (*why* do we need to have this special annotation type? i.e. why `adus` with multiple `Span`?) + - description: an `adus` may consist of several `edus`. This special annotation type allows mapping `adus` with those `Span`'s. - `LabeledAnnotationCollection` has the following fields: - `annotations` (annotation type: `Span`, target: `text`) - - `label` (str, optional), values: TODO + - `label` (str, optional), values: see [here](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L36) - `relations` (annotation type: `MultiRelation`, target: `adus`) - - description: TODO (*why* do we need to have this special annotation type? i.e. why relations with multiple `head`'s and/or `tail`'s?) + - description: some relations (e.g. `und`) involve multiple `adus` as `head` or `tail` components. This special annotation type allows `head` and `tail` to contain several `adus`. - `MultiRelation` has the following fields: - `head` (tuple, annotation type: `LabeledAnnotationCollection`, target: `adus`) - `tail` (tuple, annotation type: `LabeledAnnotationCollection`, target: `adus`) - - `label` (str, optional), values: TODO + - `label` (str, optional), values: see [here](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L37) See [here](https://github.com/ChristophAlt/pytorch-ie/blob/main/src/pytorch_ie/annotations.py) for the annotation type definitions. @@ -42,10 +42,12 @@ See [here](https://github.com/ChristophAlt/pytorch-ie/blob/main/src/pytorch_ie/a The dataset provides document converters for the following target document types: - `pytorch_ie.documents.TextDocumentWithLabeledSpansAndBinaryRelations` - - `LabeledSpans`, converted from `ArgMicroDocument`'s `adus`, labels: TODO + - `LabeledSpans`, converted from `ArgMicroDocument`'s `adus` + - labels: `opp`, `pro` - if `adus` contains multiple spans, we take the start of the first `edu` and the end of the last `edu` as the boundaries of `LabeledSpan`. We also raise exceptions when there is an overlapping. - - `BinraryRelations`, converted from `ArgMicroDocument`'s `relations`, labels: TODO - - if `relations` contains multiple `adus` as `head` and/or `tail`, then we build `BinaryRelations` between each `head`/`tail` to the other component (TODO: with which label?). Then, we build `BinaryRelations` between each component that previously belongs to the same `LabeledAnnotationCollection` (TODO: with which label?). + - `BinraryRelations`, converted from `ArgMicroDocument`'s `relations` + - labels: `sup`, `reb`, `und`, `joint`, `exa` + - if `relations` contains multiple `adus` as `head` and/or `tail`, then we build `BinaryRelations` (label taken from `relations`) between each `head`/`tail` to the other component. Then, we build `BinaryRelations`' `joint` between each component that previously belongs to the same `LabeledAnnotationCollection`. - `metadata`, we keep the `stance`, `topic_id`, and the rest of `ArgMicroDocument`'s `metadata`. See [here](https://github.com/ChristophAlt/pytorch-ie/blob/main/src/pytorch_ie/documents.py) for the document type From a8d932ef62c9088557ddf54b0a749616c24a4190 Mon Sep 17 00:00:00 2001 From: Ruangrin L <88072261+idalr@users.noreply.github.com> Date: Fri, 1 Dec 2023 15:11:33 +0100 Subject: [PATCH 19/29] created hf/readme.md --- dataset_builders/hf/HF_README.md | 177 +++++++++++++++++++++++++++++++ 1 file changed, 177 insertions(+) create mode 100644 dataset_builders/hf/HF_README.md diff --git a/dataset_builders/hf/HF_README.md b/dataset_builders/hf/HF_README.md new file mode 100644 index 00000000..aea6ee2e --- /dev/null +++ b/dataset_builders/hf/HF_README.md @@ -0,0 +1,177 @@ +# Dataset Card for "ArgMicro" + +### Dataset Summary + +The arg-microtexts corpus features 112 short argumentative texts. All texts were originally written in German and have been professionally translated to English. +Based on Freeman’s theory of the macro-structure of arguments ([1991](https://api.pageplace.de/preview/DT0400.9783110875843_A19822678/preview-9783110875843_A19822678.pdf); [2011](https://link.springer.com/book/10.1007/978-94-007-0357-5)) and Toulmin ([2003](https://www.cambridge.org/core/books/uses-of-argument/26CF801BC12004587B66778297D5567C))'s diagramming techniques, ArgMicro consists of `Pro` (proponent) and `Opp` (opponent) components and six types of relations: `Seg` (segment), `Add` (addition), `Exa` (example), `Reb` (rebut), `Sup` (support), and `Und` (undercut). It also introduced segment-based spans, which also contain non-argumentative parts, in order to cover the whole text. + +### Supported Tasks and Leaderboards + +- **Tasks:** Structure Prediction, Relation Identification, Central Claim Identification, Role Classification, Function Classification +- **Leaderboards:** \[More Information Needed\] + +### Languages + +German, with English translation (by a professional translator). + +## Dataset Structure + +### Data Instances + +- **Size of downloaded dataset files:** 2.89 MB + +``` +{ + "id": "micro_b001", + "topic_id": "waste_separation", + "stance": 1, + "text": "Yes, it's annoying and cumbersome to separate your rubbish properly all the time. Three different bin bags stink away in the kitchen and have to be sorted into different wheelie bins. But still Germany produces way too much rubbish and too many resources are lost when what actually should be separated and recycled is burnt. We Berliners should take the chance and become pioneers in waste separation!", + "edus": { + "id": ["e1", "e2", "e3", "e4", "e5"], + "start": [0, 82, 184, 232, 326], + "end": [81, 183, 231, 325, 402] + }, + "adus": { + "id": ["a1", "a2", "a3", "a4", "a5"], + "type": [0, 0, 1, 1, 1] + }, + "edges": { + "id": ["c1", "c10", "c2", "c3", "c4", "c6", "c7", "c8", "c9"], + "src": ["a1", "e5", "a2", "a3", "a4", "e1", "e2", "e3", "e4"], + "trg": ["a5", "a5", "a1", "c1", "c3", "a1", "a2", "a3", "a4"], + "type": [4, 0, 1, 5, 3, 0, 0, 0, 0] + } +} +``` + +### Data Fields + +- `id`: the instance `id` of the document, a `string` feature +- `topic_id`: the topic of the document, a `string` feature (see [list of topics](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/topics_triggers.md)) +- `stance`: the index of stance on the topic, an `int` feature (see [stance labels](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L35)) +- `text`: the text content of the document, a `string` feature +- `edus`: elementary discourse units; a segmented span of text (see the authors' further [explanation](https://github.com/peldszus/arg-microtexts/blob/master/corpus/arggraph.dtd#L17-L20)) + - `id`: the instance `id` of EDUs, a list of `string` feature + - `start`: the indices indicating the inclusive start of the spans, a list of `int` feature + - `end`: the indices indicating the exclusive end of the spans, a list of `int` feature +- `adus`: argumentative discourse units; argumentatively relevant claims built on EDUs (see the authors' further [explanation](https://github.com/peldszus/arg-microtexts/blob/master/corpus/arggraph.dtd#L22-L28)) + - `id`: the instance `id` of ADUs, a list of `string` feature + - `type`: the indices indicating the ADU type, a list of `int` feature (see [type list](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L36)) +- `edges`: the relations between `adus` or `adus` and other `edges` (see the authors' further [explanation](https://github.com/peldszus/arg-microtexts/blob/master/corpus/arggraph.dtd#L39-L47)) + - `id`: the instance `id` of edges, a list of `string` feature + - `src`: the `id` of `adus` indicating the source element in a relation, a list of `string` feature + - `trg`: the `id` of `adus` or `edges` indicating the target element in a relation, a list of `string` feature + - `type`: the indices indicating the edge type, a list of `int` feature (see [type list](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L37)) + +### Data Splits + +| | train | +| ---------------------------------------------------------- | ----------------------------: | +| No. of instances | 112 | +| No. of sentences/instance (on average) | 5.1 | +| ADUs Types
      - `pro`
      - `opp` |
      451
      125 | +| Edge Types
      - `sup`
      - `exa`
      - `reb`
      - `und` |
      263
      9
      108
      63 | + +See other corpus statistics in Peldszus ([2016](https://peldszus.github.io/files/eca2015-preprint.pdf)), Section 5. + +## Dataset Creation + +This section is composed of information and excerpts provided in Peldszus ([2016](https://peldszus.github.io/files/eca2015-preprint.pdf)). + +### Curation Rationale + +"Argumentation can, for theoretical purposes, be studied on the basis of carefully constructed examples that illustrate specific phenomena...\[We\] address this need by making a resource publicly available that is designed to fill a particular gap." (pp. 2-3) + +### Source Data + +23 texts were written by the authors as a “proof of concept” for the idea. These texts also have been used as examples in teaching and testing argumentation analysis with students. + +90 texts have been collected in a controlled text generation experiment, where normal competent language users wrote short texts of controlled linguistic and rhetoric complexity. + +#### Initial Data Collection and Normalization + +"Our contribution is a collection of 112 “microtexts” that have been written in response to trigger questions, mostly in the form of “Should one do X”. The texts are short but at the same time “complete” in that they provide a standpoint and a justification, by necessity in a fairly dense form." (p.2) + +"The probands were asked to first gather a list with the pros and cons of the trigger question, then take stance for one side and argue for it on the basis of their reflection in a short argumentative text. Each text was to fulfill three requirements: It should be about five segments long; all segments should be argumentatively relevant, either formulating the main claim of the text, supporting the main claim or another segment, or attacking the main claim or another segment. Also, the probands were asked that at least one possible objection to the claim should be considered in the text. Finally, the text should be written in such a way that it would be understandable without having its trigger question as a headline." (p.3) + +"\[A\]ll texts have been corrected for spelling and grammar errors...Their segmentation was corrected when necessary...some modifications in the remaining segments to maintain text coherence, which we made as minimal as possible." (p.4) + +"We thus constrained the translation to preserve the segmentation of the text on the one hand (effectively ruling out phrasal translations of clause-type segments) and to preserve its linearization on the other hand (disallowing changes to the order of appearance of arguments)." (p.5) + +#### Who are the source language producers? + +The texts with ids b001-b064 and k001-k031 have been collected in a controlled text generation experiment from 23 subjects discussing various controversial issues from a fixed list. All probands were native speakers of +German, of varying age, education and profession. + +The texts with ids d01-d23 have been written by Andreas Peldszus, the author. + +### Annotations + +#### Annotation process + +All texts are annotated with argumentation structures, following the scheme proposed in Peldszus & Stede ([2013](https://www.ling.uni-potsdam.de/~peldszus/ijcini2013-preprint.pdf)). For inter-annotator-agreement scores see Peldszus (2014). The (German) annotation guidelines are published in Peldszus, Warzecha, Stede (2016). See the annotation guidelines ([de](https://www.ling.uni-potsdam.de/~stede/Papers/ArgGuidelinesGerman.pdf), [en](https://www.ling.uni-potsdam.de/~stede/Papers/ArgGuidelinesEnglish.pdf)), and the [annotation schemes](https://github.com/peldszus/arg-microtexts/blob/master/corpus/arggraph.dtd). + +"\[T\]he markup of argumentation structures in the full corpus was done by one expert annotator. All annotations have been checked, controversial instances have been discussed in a reconciliation phase by two or more expert annotators...The annotation of the corpus was originally done manually on paper. In follow-up annotations, we used GraPAT ([Sonntag & Stede, 2014](http://www.lrec-conf.org/proceedings/lrec2014/pdf/824_Paper.pdf))." (p.7) + +#### Who are the annotators? + +\[More Information Needed\] + +### Personal and Sensitive Information + +\[More Information Needed\] + +## Considerations for Using the Data + +### Social Impact of Dataset + +"Automatic argumentation recognition has many possible applications, including improving document summarization (Teufel and Moens, 2002), retrieval capabilities of legal databases (Palau and Moens, 2011), opinion mining for commercial purposes, or also as a tool for assessing public +opinion on political questions. + +"...\[W\]e suggest there is yet one resource missing that could facilitate the development of automatic argumentation recognition systems: Short texts with explicit argumentation, little argumentatively irrelevant material, less rhetorical gimmicks (or even deception), in clean written language." +(Peldszus, [2014](https://aclanthology.org/W14-2112.pdf), p. 88) + +### Discussion of Biases + +\[More Information Needed\] + +### Other Known Limitations + +\[More Information Needed\] + +## Additional Information + +### Dataset Curators + +\[More Information Needed\] + +### Licensing Information + +The arg-microtexts corpus is released under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. (see [license agreement](https://creativecommons.org/licenses/by-nc-sa/4.0/)) + +### Citation Information + +``` +@inproceedings{peldszus2015annotated, + title={An annotated corpus of argumentative microtexts}, + author={Peldszus, Andreas and Stede, Manfred}, + booktitle={Argumentation and Reasoned Action: Proceedings of the 1st European Conference on Argumentation, Lisbon}, + volume={2}, + pages={801--815}, + year={2015} +} +``` + +``` +@inproceedings{peldszus2014towards, + title={Towards segment-based recognition of argumentation structure in short texts}, + author={Peldszus, Andreas}, + booktitle={Proceedings of the First Workshop on Argumentation Mining}, + pages={88--97}, + year={2014} +} +``` + +### Contributions + +Thanks to [@idalr](https://github.com/idalr) for adding this dataset. From 8bb3bad1c724d7a30db2480f65079f9ad5522816 Mon Sep 17 00:00:00 2001 From: Ruangrin L <88072261+idalr@users.noreply.github.com> Date: Fri, 1 Dec 2023 16:41:03 +0100 Subject: [PATCH 20/29] minor edit pie/readme.md --- dataset_builders/pie/argmicro/README.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/dataset_builders/pie/argmicro/README.md b/dataset_builders/pie/argmicro/README.md index be6d571a..54b06efe 100644 --- a/dataset_builders/pie/argmicro/README.md +++ b/dataset_builders/pie/argmicro/README.md @@ -21,7 +21,8 @@ The document type for this dataset is `ArgMicroDocument` which defines the follo and the following annotation layers: -- `stance` (annotation type: `Label`, see [here](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L35)) +- `stance` (annotation type: `Label`) + - description: a document may contain one of these `stance` label: `pro`, `con`, `unclear`. or no label when it is undefined. (see reference [here](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L35)) - `edus` (annotation type: `Span`, target: `text`) - `adus` (tuple, annotation type: `LabeledAnnotationCollection`, target: `edus`) - description: an `adus` may consist of several `edus`. This special annotation type allows mapping `adus` with those `Span`'s. From 416b47990dbbc78e8a8ba323c2b79d8e37435991 Mon Sep 17 00:00:00 2001 From: Arne Binder Date: Tue, 5 Dec 2023 20:22:22 +0100 Subject: [PATCH 21/29] add checks for labels counts --- tests/dataset_builders/pie/test_argmicro.py | 29 +++++++++++++++++++++ 1 file changed, 29 insertions(+) diff --git a/tests/dataset_builders/pie/test_argmicro.py b/tests/dataset_builders/pie/test_argmicro.py index 8abdecc6..1fb00398 100644 --- a/tests/dataset_builders/pie/test_argmicro.py +++ b/tests/dataset_builders/pie/test_argmicro.py @@ -265,6 +265,17 @@ def dataset() -> DatasetDict: def test_dataset(dataset): assert dataset is not None assert {name: len(ds) for name, ds in dataset.items()} == SPLIT_SIZES + for split, ds in dataset.items(): + adu_label_counts = Counter() + rel_label_counts = Counter() + for doc in ds: + adu_label_counts.update([adu.label for adu in doc.adus]) + rel_label_counts.update([rel.label for rel in doc.relations]) + if split == "train": + assert dict(adu_label_counts) == {"opp": 125, "pro": 451} + assert dict(rel_label_counts) == {"reb": 108, "sup": 263, "und": 63, "exa": 9} + else: + raise ValueError(f"Unknown split {split}") @pytest.fixture(scope="module") @@ -337,6 +348,24 @@ def test_dataset_of_text_documents_with_labeled_spans_and_binary_relations( dataset_of_text_documents_with_labeled_spans_and_binary_relations, ): assert dataset_of_text_documents_with_labeled_spans_and_binary_relations is not None + for split, ds in dataset_of_text_documents_with_labeled_spans_and_binary_relations.items(): + span_label_counts = Counter() + relation_label_counts = Counter() + for doc in ds: + span_label_counts.update([span.label for span in doc.labeled_spans]) + relation_label_counts.update([rel.label for rel in doc.binary_relations]) + if split == "train": + assert dict(span_label_counts) == {"opp": 125, "pro": 451} + assert dict(relation_label_counts) == { + "reb": 110, + "sup": 281, + "und": 65, + "joint": 44, + "exa": 9, + } + else: + raise ValueError(f"Unknown split {split}") + # get a document to check converted_doc = dataset_of_text_documents_with_labeled_spans_and_binary_relations["train"][0] From f44c4ede71320cf131cc88d78aa5916c3535603e Mon Sep 17 00:00:00 2001 From: Arne Binder Date: Tue, 5 Dec 2023 20:22:58 +0100 Subject: [PATCH 22/29] polish PIE dataset card --- dataset_builders/pie/argmicro/README.md | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/dataset_builders/pie/argmicro/README.md b/dataset_builders/pie/argmicro/README.md index 54b06efe..6b009938 100644 --- a/dataset_builders/pie/argmicro/README.md +++ b/dataset_builders/pie/argmicro/README.md @@ -1,4 +1,4 @@ -# PIE Dataset Card for "ArgMicro" +# PIE Dataset Card for "argmicro" This is a [PyTorch-IE](https://github.com/ChristophAlt/pytorch-ie) wrapper for the [ArgMicro Huggingface dataset loading script](https://huggingface.co/datasets/DFKI-SLT/argmicro). @@ -22,19 +22,19 @@ The document type for this dataset is `ArgMicroDocument` which defines the follo and the following annotation layers: - `stance` (annotation type: `Label`) - - description: a document may contain one of these `stance` label: `pro`, `con`, `unclear`. or no label when it is undefined. (see reference [here](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L35)) + - description: A document may contain one of these `stance` labels: `pro`, `con`, `unclear`, or no label when it is undefined (see [here](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L35) for reference). - `edus` (annotation type: `Span`, target: `text`) - `adus` (tuple, annotation type: `LabeledAnnotationCollection`, target: `edus`) - - description: an `adus` may consist of several `edus`. This special annotation type allows mapping `adus` with those `Span`'s. + - description: each element of `adus` may consist of several entries from `edus`, so we require `LabeledAnnotationCollection` as annotation type. This is originally indicated by `seg` edges in the data. - `LabeledAnnotationCollection` has the following fields: - `annotations` (annotation type: `Span`, target: `text`) - - `label` (str, optional), values: see [here](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L36) + - `label` (str, optional), values: `opp`, `pro` (see [here](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L36)) - `relations` (annotation type: `MultiRelation`, target: `adus`) - - description: some relations (e.g. `und`) involve multiple `adus` as `head` or `tail` components. This special annotation type allows `head` and `tail` to contain several `adus`. + - description: Undercut (`und`) relations originally target other relations (i.e. edges), but we let them target the `head` of the targeted relation instead. The original state can be deterministically reconstructed by taking the label into account. Furthermore, the head of additional source (`add`) relations are integrated into the head of the target relation (note that this propagates along `und` relations). We model this with `MultiRelation`s whose `head` and `tail` are of type `LabeledAnnotationCollection`. - `MultiRelation` has the following fields: - `head` (tuple, annotation type: `LabeledAnnotationCollection`, target: `adus`) - `tail` (tuple, annotation type: `LabeledAnnotationCollection`, target: `adus`) - - `label` (str, optional), values: see [here](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L37) + - `label` (str, optional), values: `sup`, `exa`, `reb`, `und` (see [here](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L37) for reference, but note that helper relations `seg` and `add` are not there anymore, see above). See [here](https://github.com/ChristophAlt/pytorch-ie/blob/main/src/pytorch_ie/annotations.py) for the annotation type definitions. @@ -45,11 +45,11 @@ The dataset provides document converters for the following target document types - `pytorch_ie.documents.TextDocumentWithLabeledSpansAndBinaryRelations` - `LabeledSpans`, converted from `ArgMicroDocument`'s `adus` - labels: `opp`, `pro` - - if `adus` contains multiple spans, we take the start of the first `edu` and the end of the last `edu` as the boundaries of `LabeledSpan`. We also raise exceptions when there is an overlapping. + - if an ADU contains multiple spans (i.e. EDUs), we take the start of the first EDU and the end of the last EDU as the boundaries of the new `LabeledSpan`. We also raise exceptions if any newly created `LabeledSpan`s overlap. - `BinraryRelations`, converted from `ArgMicroDocument`'s `relations` - labels: `sup`, `reb`, `und`, `joint`, `exa` - - if `relations` contains multiple `adus` as `head` and/or `tail`, then we build `BinaryRelations` (label taken from `relations`) between each `head`/`tail` to the other component. Then, we build `BinaryRelations`' `joint` between each component that previously belongs to the same `LabeledAnnotationCollection`. - - `metadata`, we keep the `stance`, `topic_id`, and the rest of `ArgMicroDocument`'s `metadata`. + - if the `head` or `tail` consists of multiple `adus`, then we build `BinaryRelation`s with all `head`-`tail` combinations and take the label from the original relation. Then, we build `BinaryRelations`' with label `joint` between each component that previously belongs to the same `head` or `tail`, respectively. + - `metadata`, we keep the `ArgMicroDocument`'s `metadata`, but `stance` and `topic_id`. See [here](https://github.com/ChristophAlt/pytorch-ie/blob/main/src/pytorch_ie/documents.py) for the document type definitions. From 2ff167c74a38ce35caff6717f5ae09a611aa6bad Mon Sep 17 00:00:00 2001 From: Arne Binder Date: Tue, 5 Dec 2023 20:25:52 +0100 Subject: [PATCH 23/29] minor --- dataset_builders/pie/argmicro/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/dataset_builders/pie/argmicro/README.md b/dataset_builders/pie/argmicro/README.md index 6b009938..c8fa590f 100644 --- a/dataset_builders/pie/argmicro/README.md +++ b/dataset_builders/pie/argmicro/README.md @@ -14,8 +14,8 @@ The dataset contains two `BuilderConfig`'s: The document type for this dataset is `ArgMicroDocument` which defines the following data fields: -- `id` (str) - `text` (str) +- `id` (str, optional) - `topic_id` (str, optional) - `metadata` (dictionary, optional) From b615661b3e40b14a83a4dbd2fbd666611f98f2a1 Mon Sep 17 00:00:00 2001 From: Arne Binder Date: Tue, 5 Dec 2023 21:13:08 +0100 Subject: [PATCH 24/29] minor fix --- dataset_builders/pie/argmicro/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/dataset_builders/pie/argmicro/README.md b/dataset_builders/pie/argmicro/README.md index c8fa590f..fe9da6f9 100644 --- a/dataset_builders/pie/argmicro/README.md +++ b/dataset_builders/pie/argmicro/README.md @@ -24,7 +24,7 @@ and the following annotation layers: - `stance` (annotation type: `Label`) - description: A document may contain one of these `stance` labels: `pro`, `con`, `unclear`, or no label when it is undefined (see [here](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L35) for reference). - `edus` (annotation type: `Span`, target: `text`) -- `adus` (tuple, annotation type: `LabeledAnnotationCollection`, target: `edus`) +- `adus` (annotation type: `LabeledAnnotationCollection`, target: `edus`) - description: each element of `adus` may consist of several entries from `edus`, so we require `LabeledAnnotationCollection` as annotation type. This is originally indicated by `seg` edges in the data. - `LabeledAnnotationCollection` has the following fields: - `annotations` (annotation type: `Span`, target: `text`) From 33b09cc1512cf03cc227779c05aa36b41f0fe522 Mon Sep 17 00:00:00 2001 From: Arne Binder Date: Tue, 5 Dec 2023 21:17:38 +0100 Subject: [PATCH 25/29] add stance label count test --- tests/dataset_builders/pie/test_argmicro.py | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/tests/dataset_builders/pie/test_argmicro.py b/tests/dataset_builders/pie/test_argmicro.py index 1fb00398..9fa85e4e 100644 --- a/tests/dataset_builders/pie/test_argmicro.py +++ b/tests/dataset_builders/pie/test_argmicro.py @@ -266,12 +266,18 @@ def test_dataset(dataset): assert dataset is not None assert {name: len(ds) for name, ds in dataset.items()} == SPLIT_SIZES for split, ds in dataset.items(): + stance_label_counts = Counter() adu_label_counts = Counter() rel_label_counts = Counter() for doc in ds: + assert len(doc.stance) <= 1 + stance_label_counts.update([stance.label for stance in doc.stance]) + if len(doc.stance) == 0: + stance_label_counts.update(["UNDEFINED"]) adu_label_counts.update([adu.label for adu in doc.adus]) rel_label_counts.update([rel.label for rel in doc.relations]) if split == "train": + assert dict(stance_label_counts) == {'pro': 46, 'con': 42, 'UNDEFINED': 23, 'unclear': 1} assert dict(adu_label_counts) == {"opp": 125, "pro": 451} assert dict(rel_label_counts) == {"reb": 108, "sup": 263, "und": 63, "exa": 9} else: From 9badaaaaa5b9b1460712f75983b9e7cb78ff0f0e Mon Sep 17 00:00:00 2001 From: Arne Binder Date: Tue, 5 Dec 2023 21:18:11 +0100 Subject: [PATCH 26/29] make pre-commit happy --- tests/dataset_builders/pie/test_argmicro.py | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/tests/dataset_builders/pie/test_argmicro.py b/tests/dataset_builders/pie/test_argmicro.py index 9fa85e4e..4d441bc5 100644 --- a/tests/dataset_builders/pie/test_argmicro.py +++ b/tests/dataset_builders/pie/test_argmicro.py @@ -277,7 +277,12 @@ def test_dataset(dataset): adu_label_counts.update([adu.label for adu in doc.adus]) rel_label_counts.update([rel.label for rel in doc.relations]) if split == "train": - assert dict(stance_label_counts) == {'pro': 46, 'con': 42, 'UNDEFINED': 23, 'unclear': 1} + assert dict(stance_label_counts) == { + "pro": 46, + "con": 42, + "UNDEFINED": 23, + "unclear": 1, + } assert dict(adu_label_counts) == {"opp": 125, "pro": 451} assert dict(rel_label_counts) == {"reb": 108, "sup": 263, "und": 63, "exa": 9} else: From c99e3d6f1a1b8a3d3541b5720297781392f41fe9 Mon Sep 17 00:00:00 2001 From: Ruangrin L <88072261+idalr@users.noreply.github.com> Date: Thu, 7 Dec 2023 15:08:06 +0100 Subject: [PATCH 27/29] edit hf/readme.md --- .../hf/{ => argmicro}/HF_README.md | 44 ++++++++++++++++++- 1 file changed, 42 insertions(+), 2 deletions(-) rename dataset_builders/hf/{ => argmicro}/HF_README.md (85%) diff --git a/dataset_builders/hf/HF_README.md b/dataset_builders/hf/argmicro/HF_README.md similarity index 85% rename from dataset_builders/hf/HF_README.md rename to dataset_builders/hf/argmicro/HF_README.md index aea6ee2e..010c5163 100644 --- a/dataset_builders/hf/HF_README.md +++ b/dataset_builders/hf/argmicro/HF_README.md @@ -69,8 +69,48 @@ German, with English translation (by a professional translator). | ---------------------------------------------------------- | ----------------------------: | | No. of instances | 112 | | No. of sentences/instance (on average) | 5.1 | -| ADUs Types
      - `pro`
      - `opp` |
      451
      125 | -| Edge Types
      - `sup`
      - `exa`
      - `reb`
      - `und` |
      263
      9
      108
      63 | + + +### Data Labels + +| Stance | Count | Percentage | +|-------------|------:|-----------:| +| `pro` | 46 | 41.1 % | +| `con` | 42 | 37.5 % | +| `unclear` | 1 | 0.9 % | +| `UNDEFINED` | 23 | 20.5 % | + +#TODO + - `pro`: + - `con`: + - `unclear`: + - `UNDEFINED`: + +| ADUs | Count | Percentage | +|-------| ----: | ---------: | +| `Pro` | 451 | 78.3 % | +| `Opp` | 125 | 21.7 % | + + - `pro`: proponent, who presents and defends his claims + - `opp`: oppponent, who critically questions the proponent in a regimented fashion (P&S, 2015, p.5) + +| Relations | Count | Percentage | +|----------------|------:|-----------:| +| support: `sup` | 281 | 55.2 % | +| support: `exa` | 9 | 1.8 % | +| attack: `und` | 65 | 12.8 % | +| attack: `reb` | 110 | 21.6 % | +| other: `joint` | 44 | 8.6 % | + + - `sup`: support (ADU->ADU) + - `exa`: support by example (ADU->ADU) + - `add`: additional source, for combined/convergent arguments with multiple premises, i.e., linked support, convergent support, serial support (ADU->ADU) + - `reb`: rebutting attack (ADU->ADU) + - definition: "targeting another node and thereby challenging its acceptability" + - `und`: undercutting attack (ADU->Edge) + - definition: "targeting an edge and thereby challenging the acceptability of the inference from the source to the target node" + ([P&S, 2016](https://github.com/peldszus/arg-microtexts/blob/master/corpus/arggraph.dtd), [P&S, EN annotation guideline](https://www.ling.uni-potsdam.de/~stede/Papers/ArgGuidelinesEnglish.pdf)) + - `joint`: combines text segments if one does not express a complete proposition on its own, or if the author divides a clause/sentence into parts, using punctuation See other corpus statistics in Peldszus ([2016](https://peldszus.github.io/files/eca2015-preprint.pdf)), Section 5. From ec595c484c7a0935c7aa8ba9136d3e5bf0bb1834 Mon Sep 17 00:00:00 2001 From: Ruangrin L <88072261+idalr@users.noreply.github.com> Date: Thu, 7 Dec 2023 16:21:33 +0100 Subject: [PATCH 28/29] updated `BASE_DATASET_REVISION` to latest commit --- dataset_builders/pie/argmicro/argmicro.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/dataset_builders/pie/argmicro/argmicro.py b/dataset_builders/pie/argmicro/argmicro.py index 5bc2da26..f6c20578 100644 --- a/dataset_builders/pie/argmicro/argmicro.py +++ b/dataset_builders/pie/argmicro/argmicro.py @@ -268,7 +268,7 @@ class ArgMicro(GeneratorBasedBuilder): } BASE_DATASET_PATH = "DFKI-SLT/argmicro" - BASE_DATASET_REVISION = "22958d585f5c0c646c81ac62947bdf6cf9ab3cc5" + BASE_DATASET_REVISION = "282733d6d57243f2a202d81143c4e31bb250e663" BUILDER_CONFIGS = [datasets.BuilderConfig(name="en"), datasets.BuilderConfig(name="de")] From 8f2e6a61f2483ac4dea43962c4c2e2eab99a9a6a Mon Sep 17 00:00:00 2001 From: Ruangrin L <88072261+idalr@users.noreply.github.com> Date: Thu, 7 Dec 2023 16:25:54 +0100 Subject: [PATCH 29/29] removed hf dataset card --- dataset_builders/hf/argmicro/HF_README.md | 217 ---------------------- 1 file changed, 217 deletions(-) delete mode 100644 dataset_builders/hf/argmicro/HF_README.md diff --git a/dataset_builders/hf/argmicro/HF_README.md b/dataset_builders/hf/argmicro/HF_README.md deleted file mode 100644 index 010c5163..00000000 --- a/dataset_builders/hf/argmicro/HF_README.md +++ /dev/null @@ -1,217 +0,0 @@ -# Dataset Card for "ArgMicro" - -### Dataset Summary - -The arg-microtexts corpus features 112 short argumentative texts. All texts were originally written in German and have been professionally translated to English. -Based on Freeman’s theory of the macro-structure of arguments ([1991](https://api.pageplace.de/preview/DT0400.9783110875843_A19822678/preview-9783110875843_A19822678.pdf); [2011](https://link.springer.com/book/10.1007/978-94-007-0357-5)) and Toulmin ([2003](https://www.cambridge.org/core/books/uses-of-argument/26CF801BC12004587B66778297D5567C))'s diagramming techniques, ArgMicro consists of `Pro` (proponent) and `Opp` (opponent) components and six types of relations: `Seg` (segment), `Add` (addition), `Exa` (example), `Reb` (rebut), `Sup` (support), and `Und` (undercut). It also introduced segment-based spans, which also contain non-argumentative parts, in order to cover the whole text. - -### Supported Tasks and Leaderboards - -- **Tasks:** Structure Prediction, Relation Identification, Central Claim Identification, Role Classification, Function Classification -- **Leaderboards:** \[More Information Needed\] - -### Languages - -German, with English translation (by a professional translator). - -## Dataset Structure - -### Data Instances - -- **Size of downloaded dataset files:** 2.89 MB - -``` -{ - "id": "micro_b001", - "topic_id": "waste_separation", - "stance": 1, - "text": "Yes, it's annoying and cumbersome to separate your rubbish properly all the time. Three different bin bags stink away in the kitchen and have to be sorted into different wheelie bins. But still Germany produces way too much rubbish and too many resources are lost when what actually should be separated and recycled is burnt. We Berliners should take the chance and become pioneers in waste separation!", - "edus": { - "id": ["e1", "e2", "e3", "e4", "e5"], - "start": [0, 82, 184, 232, 326], - "end": [81, 183, 231, 325, 402] - }, - "adus": { - "id": ["a1", "a2", "a3", "a4", "a5"], - "type": [0, 0, 1, 1, 1] - }, - "edges": { - "id": ["c1", "c10", "c2", "c3", "c4", "c6", "c7", "c8", "c9"], - "src": ["a1", "e5", "a2", "a3", "a4", "e1", "e2", "e3", "e4"], - "trg": ["a5", "a5", "a1", "c1", "c3", "a1", "a2", "a3", "a4"], - "type": [4, 0, 1, 5, 3, 0, 0, 0, 0] - } -} -``` - -### Data Fields - -- `id`: the instance `id` of the document, a `string` feature -- `topic_id`: the topic of the document, a `string` feature (see [list of topics](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/topics_triggers.md)) -- `stance`: the index of stance on the topic, an `int` feature (see [stance labels](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L35)) -- `text`: the text content of the document, a `string` feature -- `edus`: elementary discourse units; a segmented span of text (see the authors' further [explanation](https://github.com/peldszus/arg-microtexts/blob/master/corpus/arggraph.dtd#L17-L20)) - - `id`: the instance `id` of EDUs, a list of `string` feature - - `start`: the indices indicating the inclusive start of the spans, a list of `int` feature - - `end`: the indices indicating the exclusive end of the spans, a list of `int` feature -- `adus`: argumentative discourse units; argumentatively relevant claims built on EDUs (see the authors' further [explanation](https://github.com/peldszus/arg-microtexts/blob/master/corpus/arggraph.dtd#L22-L28)) - - `id`: the instance `id` of ADUs, a list of `string` feature - - `type`: the indices indicating the ADU type, a list of `int` feature (see [type list](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L36)) -- `edges`: the relations between `adus` or `adus` and other `edges` (see the authors' further [explanation](https://github.com/peldszus/arg-microtexts/blob/master/corpus/arggraph.dtd#L39-L47)) - - `id`: the instance `id` of edges, a list of `string` feature - - `src`: the `id` of `adus` indicating the source element in a relation, a list of `string` feature - - `trg`: the `id` of `adus` or `edges` indicating the target element in a relation, a list of `string` feature - - `type`: the indices indicating the edge type, a list of `int` feature (see [type list](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L37)) - -### Data Splits - -| | train | -| ---------------------------------------------------------- | ----------------------------: | -| No. of instances | 112 | -| No. of sentences/instance (on average) | 5.1 | - - -### Data Labels - -| Stance | Count | Percentage | -|-------------|------:|-----------:| -| `pro` | 46 | 41.1 % | -| `con` | 42 | 37.5 % | -| `unclear` | 1 | 0.9 % | -| `UNDEFINED` | 23 | 20.5 % | - -#TODO - - `pro`: - - `con`: - - `unclear`: - - `UNDEFINED`: - -| ADUs | Count | Percentage | -|-------| ----: | ---------: | -| `Pro` | 451 | 78.3 % | -| `Opp` | 125 | 21.7 % | - - - `pro`: proponent, who presents and defends his claims - - `opp`: oppponent, who critically questions the proponent in a regimented fashion (P&S, 2015, p.5) - -| Relations | Count | Percentage | -|----------------|------:|-----------:| -| support: `sup` | 281 | 55.2 % | -| support: `exa` | 9 | 1.8 % | -| attack: `und` | 65 | 12.8 % | -| attack: `reb` | 110 | 21.6 % | -| other: `joint` | 44 | 8.6 % | - - - `sup`: support (ADU->ADU) - - `exa`: support by example (ADU->ADU) - - `add`: additional source, for combined/convergent arguments with multiple premises, i.e., linked support, convergent support, serial support (ADU->ADU) - - `reb`: rebutting attack (ADU->ADU) - - definition: "targeting another node and thereby challenging its acceptability" - - `und`: undercutting attack (ADU->Edge) - - definition: "targeting an edge and thereby challenging the acceptability of the inference from the source to the target node" - ([P&S, 2016](https://github.com/peldszus/arg-microtexts/blob/master/corpus/arggraph.dtd), [P&S, EN annotation guideline](https://www.ling.uni-potsdam.de/~stede/Papers/ArgGuidelinesEnglish.pdf)) - - `joint`: combines text segments if one does not express a complete proposition on its own, or if the author divides a clause/sentence into parts, using punctuation - -See other corpus statistics in Peldszus ([2016](https://peldszus.github.io/files/eca2015-preprint.pdf)), Section 5. - -## Dataset Creation - -This section is composed of information and excerpts provided in Peldszus ([2016](https://peldszus.github.io/files/eca2015-preprint.pdf)). - -### Curation Rationale - -"Argumentation can, for theoretical purposes, be studied on the basis of carefully constructed examples that illustrate specific phenomena...\[We\] address this need by making a resource publicly available that is designed to fill a particular gap." (pp. 2-3) - -### Source Data - -23 texts were written by the authors as a “proof of concept” for the idea. These texts also have been used as examples in teaching and testing argumentation analysis with students. - -90 texts have been collected in a controlled text generation experiment, where normal competent language users wrote short texts of controlled linguistic and rhetoric complexity. - -#### Initial Data Collection and Normalization - -"Our contribution is a collection of 112 “microtexts” that have been written in response to trigger questions, mostly in the form of “Should one do X”. The texts are short but at the same time “complete” in that they provide a standpoint and a justification, by necessity in a fairly dense form." (p.2) - -"The probands were asked to first gather a list with the pros and cons of the trigger question, then take stance for one side and argue for it on the basis of their reflection in a short argumentative text. Each text was to fulfill three requirements: It should be about five segments long; all segments should be argumentatively relevant, either formulating the main claim of the text, supporting the main claim or another segment, or attacking the main claim or another segment. Also, the probands were asked that at least one possible objection to the claim should be considered in the text. Finally, the text should be written in such a way that it would be understandable without having its trigger question as a headline." (p.3) - -"\[A\]ll texts have been corrected for spelling and grammar errors...Their segmentation was corrected when necessary...some modifications in the remaining segments to maintain text coherence, which we made as minimal as possible." (p.4) - -"We thus constrained the translation to preserve the segmentation of the text on the one hand (effectively ruling out phrasal translations of clause-type segments) and to preserve its linearization on the other hand (disallowing changes to the order of appearance of arguments)." (p.5) - -#### Who are the source language producers? - -The texts with ids b001-b064 and k001-k031 have been collected in a controlled text generation experiment from 23 subjects discussing various controversial issues from a fixed list. All probands were native speakers of -German, of varying age, education and profession. - -The texts with ids d01-d23 have been written by Andreas Peldszus, the author. - -### Annotations - -#### Annotation process - -All texts are annotated with argumentation structures, following the scheme proposed in Peldszus & Stede ([2013](https://www.ling.uni-potsdam.de/~peldszus/ijcini2013-preprint.pdf)). For inter-annotator-agreement scores see Peldszus (2014). The (German) annotation guidelines are published in Peldszus, Warzecha, Stede (2016). See the annotation guidelines ([de](https://www.ling.uni-potsdam.de/~stede/Papers/ArgGuidelinesGerman.pdf), [en](https://www.ling.uni-potsdam.de/~stede/Papers/ArgGuidelinesEnglish.pdf)), and the [annotation schemes](https://github.com/peldszus/arg-microtexts/blob/master/corpus/arggraph.dtd). - -"\[T\]he markup of argumentation structures in the full corpus was done by one expert annotator. All annotations have been checked, controversial instances have been discussed in a reconciliation phase by two or more expert annotators...The annotation of the corpus was originally done manually on paper. In follow-up annotations, we used GraPAT ([Sonntag & Stede, 2014](http://www.lrec-conf.org/proceedings/lrec2014/pdf/824_Paper.pdf))." (p.7) - -#### Who are the annotators? - -\[More Information Needed\] - -### Personal and Sensitive Information - -\[More Information Needed\] - -## Considerations for Using the Data - -### Social Impact of Dataset - -"Automatic argumentation recognition has many possible applications, including improving document summarization (Teufel and Moens, 2002), retrieval capabilities of legal databases (Palau and Moens, 2011), opinion mining for commercial purposes, or also as a tool for assessing public -opinion on political questions. - -"...\[W\]e suggest there is yet one resource missing that could facilitate the development of automatic argumentation recognition systems: Short texts with explicit argumentation, little argumentatively irrelevant material, less rhetorical gimmicks (or even deception), in clean written language." -(Peldszus, [2014](https://aclanthology.org/W14-2112.pdf), p. 88) - -### Discussion of Biases - -\[More Information Needed\] - -### Other Known Limitations - -\[More Information Needed\] - -## Additional Information - -### Dataset Curators - -\[More Information Needed\] - -### Licensing Information - -The arg-microtexts corpus is released under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. (see [license agreement](https://creativecommons.org/licenses/by-nc-sa/4.0/)) - -### Citation Information - -``` -@inproceedings{peldszus2015annotated, - title={An annotated corpus of argumentative microtexts}, - author={Peldszus, Andreas and Stede, Manfred}, - booktitle={Argumentation and Reasoned Action: Proceedings of the 1st European Conference on Argumentation, Lisbon}, - volume={2}, - pages={801--815}, - year={2015} -} -``` - -``` -@inproceedings{peldszus2014towards, - title={Towards segment-based recognition of argumentation structure in short texts}, - author={Peldszus, Andreas}, - booktitle={Proceedings of the First Workshop on Argumentation Mining}, - pages={88--97}, - year={2014} -} -``` - -### Contributions - -Thanks to [@idalr](https://github.com/idalr) for adding this dataset.

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