- State of the art LSTM architectures using NN
- Medium: Ner free datasets and bilstm implementation using glove embeddings
- Easy to implement in keras! They are based on the following paper
- Medium: NLTK entities, polyglot entities, sner entities, finally an ensemble method wins all!
- Comparison between spacy and SNER - for terms.
- *** Unsupervised NER using Bert
- Custom NER using spacy
- Spacy Ner with custom data
- How to create a NER from scratch using kaggle data, using crf, and analysing crf weights using external package
- Another comparison between spacy and SNER - both are the same, for many classes.
- Vidhaya on spacy vs ner - tutorial + code on how to use spacy for pos, dep, ner, compared to nltk/corenlp (sner etc). The results reflect a global score not specific to LOC for example.
Stanford NER (SNER)
- SNER presentation - combines HMM and MaxEnt features, distributional features, NER has
- many applications.
- How to train SNER, a FAQ with many other answers (read first before doing anything with SNER)
- SNER demo - capital letters matter, a minimum of one.
- State of the art NER benchmark
- Review paper, SNER, spacy, stanford wins
- Review paper SNER, others on biographical text, stanford wins
- Another NER DL paper, 90%+
Spacy & Others
- Spacy - using prodigy and spacy to train a NER classifier using active learning
- Ner using DL BLSTM, using glove embeddings, using CRF layer against another CRF.
- Another medium paper on the BLSTM CRF with guillarue’s code
- Guillaume blog post, detailed explanation
- For Italian
- Another 90+ proposed solution
- A promising python implementation based on one or two of the previous papers
- Quora advise, the first is cool, the second is questionable
- Off the shelf solutions benchmark
- Parallel api talk about bilstm and their 2mil tagged ner model (washington passes)