Create NER.md

docs/NER.md

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+# NER model
+
+This page will collect the Model Cards for NER in PyThaiNLP.
+
+## Thai NER
+
+### v1.4
+
+**Model Details**
+
+- Developer: Wannaphong Phatthiyaphaibun
+- This report author: Wannaphong Phatthiyaphaibun
+- Model date: 2020-5-21
+- Model version: 1.4
+- Used in PyThaiNLP version: 2.2 +
+- Filename: `~/pythainlp-data/thai-ner-1-4.crfsuite`
+- CRF Model
+- License: CC0
+- GitHub for Thai NER 1.4 (Data and train notebook): [https://github.com/wannaphong/thai-ner/tree/master/model/1.4](https://github.com/wannaphong/thai-ner/tree/master/model/1.4)
+
+**Intended Use**
+
+- Named-Entity Tagging for Thai.
+- Not suitable for other language or non-news domain.
+
+**Factors**
+
+- Based on known problems with thai natural Language processing.
+
+**Metrics**
+
+- Evaluation metrics include precision, recall and f1-score.
+
+**Training Data**
+
+ThaiNER 1.3 Corpus Train set
+
+**Evaluation Data**
+
+ThaiNER 1.3 Corpus Test set
+
+**Quantitative Analyses**
+
+```
+
+ precision recall f1-score support
+
+ B-DATE 0.92 0.86 0.89 375
+ I-DATE 0.94 0.94 0.94 747
+ B-EMAIL 1.00 1.00 1.00 5
+ I-EMAIL 1.00 1.00 1.00 28
+ B-LAW 0.71 0.56 0.62 43
+ I-LAW 0.74 0.70 0.72 154
+ B-LEN 0.96 0.93 0.95 29
+ I-LEN 0.98 0.94 0.96 69
+ B-LOCATION 0.88 0.77 0.82 864
+ I-LOCATION 0.86 0.73 0.79 852
+ B-MONEY 0.98 0.85 0.91 105
+ I-MONEY 0.96 0.95 0.95 239
+B-ORGANIZATION 0.90 0.78 0.84 1166
+I-ORGANIZATION 0.84 0.77 0.81 1338
+ B-PERCENT 1.00 0.97 0.99 34
+ I-PERCENT 1.00 0.96 0.98 51
+ B-PERSON 0.96 0.82 0.88 676
+ I-PERSON 0.94 0.92 0.93 2424
+ B-PHONE 1.00 0.72 0.84 29
+ I-PHONE 0.96 0.92 0.94 78
+ B-TIME 0.87 0.73 0.79 172
+ I-TIME 0.94 0.83 0.88 336
+ B-URL 0.89 1.00 0.94 24
+ I-URL 0.96 1.00 0.98 371
+ B-ZIP 1.00 1.00 1.00 4
+
+ micro avg 0.91 0.84 0.87 10213
+ macro avg 0.93 0.87 0.89 10213
+ weighted avg 0.91 0.84 0.87 10213
+ samples avg 0.17 0.17 0.17 10213
+```
+
+**Ethical Considerations**
+
+- This model has bias from corpus creator. (Wannaphong Phatthiyaphaibun)
+- This model uses the part-of-speech model to build it, so It does have a bias from the part-of-speech model.
+
+
+**Caveats and Recommendations**
+
+- Thai text only
+
+
+### v1.5
+
+**Model Details**
+
+- Developer: Wannaphong Phatthiyaphaibun
+- This report author: Wannaphong Phatthiyaphaibun
+- Model date: 2021-1-16
+- Model version: 1.5
+- Used in PyThaiNLP version: 2.3 +
+- Filename: `~/pythainlp-data/thai-ner-1-5-newmm-lst20.crfsuite`
+- CRF Model
+- License: CC0
+- GitHub for Thai NER 1.5 (Data and train notebook): `thai-ner-1-5-newmm-lst20.ipynb` [https://github.com/wannaphong/thai-ner/tree/master/model/1.5](https://github.com/wannaphong/thai-ner/tree/master/model/1.5)
+
+**Intended Use**
+
+- Named-Entity Tagging for Thai.
+- Not suitable for other language or non-news domain.
+
+**Factors**
+
+- Based on known problems with thai natural Language processing.
+
+**Metrics**
+
+- Evaluation metrics include precision, recall and f1-score.
+
+**Training Data**
+
+ThaiNER 1.5 Corpus Train set (5089 sent)
+
+**Evaluation Data**
+
+ThaiNER 1.5 Corpus Test set (1274 sent)
+
+**Quantitative Analyses**
+
+```
+ precision recall f1-score support
+
+ B-DATE 0.93 0.82 0.87 350
+ I-DATE 0.95 0.94 0.95 665
+ B-LAW 0.85 0.54 0.66 87
+ I-LAW 0.85 0.64 0.73 253
+ B-LEN 1.00 0.75 0.86 12
+ I-LEN 1.00 0.69 0.82 26
+ B-LOCATION 0.81 0.70 0.75 620
+ I-LOCATION 0.74 0.72 0.73 533
+ B-MONEY 1.00 0.91 0.95 131
+ I-MONEY 0.99 0.95 0.97 321
+B-ORGANIZATION 0.92 0.70 0.80 1334
+I-ORGANIZATION 0.80 0.73 0.76 1198
+ B-PERCENT 0.94 0.88 0.91 17
+ I-PERCENT 0.91 0.95 0.93 22
+ B-PERSON 0.96 0.78 0.86 607
+ I-PERSON 0.94 0.88 0.91 2181
+ B-PHONE 1.00 0.50 0.67 2
+ I-PHONE 1.00 1.00 1.00 8
+ B-TIME 0.93 0.66 0.77 87
+ I-TIME 0.97 0.77 0.86 158
+ B-URL 0.91 0.83 0.87 12
+ I-URL 0.93 0.96 0.94 94
+
+ micro avg 0.89 0.79 0.84 8718
+ macro avg 0.92 0.79 0.84 8718
+ weighted avg 0.90 0.79 0.84 8718
+ samples avg 0.16 0.16 0.16 8718
+```
+
+**Ethical Considerations**
+
+- This model has bias from corpus creator. (Wannaphong Phatthiyaphaibun)
+- This model uses the part-of-speech model to build it, so It does have a bias from the part-of-speech model.
+
+**Caveats and Recommendations**
+
+- Thai text only
+
+## v1.5.1
+
+**Model Details**
+
+- Developer: Wannaphong Phatthiyaphaibun
+- This report author: Wannaphong Phatthiyaphaibun
+- Model date: 2021-6-21
+- Model version: 1.5.1
+- Used in PyThaiNLP version: 2.4 +
+- Filename: `pythainlp/corpus/thainer_crf_1_5_1.model`
+- CRF Model
+- License: CC0
+- GitHub for Thai NER 1.5.1 (Data and train notebook): [https://github.com/wannaphong/thai-ner/tree/master/model/1.5.1](https://github.com/wannaphong/thai-ner/tree/master/model/1.5.1)
+
+**Intended Use**
+
+- Named-Entity Tagging for Thai.
+- Not suitable for other language or non-news domain.
+
+**Factors**
+
+- Based on known problems with thai natural Language processing.
+
+**Metrics**
+
+- Evaluation metrics include precision, recall and f1-score.
+
+**Training Data**
+
+ThaiNER 1.5 Corpus Train set (5089 sent)
+
+**Evaluation Data**
+
+ThaiNER 1.5 Corpus Test set (1274 sent)
+
+**Quantitative Analyses**
+
+```
+
+
+ precision recall f1-score support
+
+ B-DATE 0.93 0.81 0.87 350
+ I-DATE 0.94 0.94 0.94 665
+ B-LAW 0.85 0.54 0.66 87
+ I-LAW 0.87 0.65 0.74 253
+ B-LEN 1.00 0.75 0.86 12
+ I-LEN 1.00 0.69 0.82 26
+ B-LOCATION 0.80 0.70 0.75 620
+ I-LOCATION 0.75 0.72 0.73 533
+ B-MONEY 1.00 0.90 0.95 131
+ I-MONEY 0.99 0.94 0.97 321
+B-ORGANIZATION 0.91 0.70 0.79 1334
+I-ORGANIZATION 0.80 0.73 0.76 1198
+ B-PERCENT 0.94 0.88 0.91 17
+ I-PERCENT 0.91 0.95 0.93 22
+ B-PERSON 0.96 0.78 0.86 607
+ I-PERSON 0.94 0.88 0.91 2181
+ B-PHONE 1.00 0.50 0.67 2
+ I-PHONE 1.00 1.00 1.00 8
+ B-TIME 0.93 0.66 0.77 87
+ I-TIME 0.97 0.77 0.86 158
+ B-URL 0.91 0.83 0.87 12
+ I-URL 0.93 0.96 0.94 94
+
+ micro avg 0.89 0.79 0.84 8718
+ macro avg 0.92 0.79 0.84 8718
+ weighted avg 0.89 0.79 0.84 8718
+ samples avg 0.16 0.16 0.16 8718
+```
+
+**Ethical Considerations**
+
+- This model has bias from corpus creator. (Wannaphong Phatthiyaphaibun)
+- This model uses the part-of-speech model to build it, so It does have a bias from the part-of-speech model.
+
+**Caveats and Recommendations**
+
+- Thai text only
+
+### v2.0
+
+Host: [https://huggingface.co/pythainlp/thainer-corpus-v2-base-model](https://huggingface.co/pythainlp/thainer-corpus-v2-base-model)