A fork edit version of https://github.com/Determined22/zh-NER-TF By add Other Features and Char embedding layer on English Corpus
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NER is a basic task in NLP. This a fork edit version of https://github.com/Determined22/zh-NER-TF By add Other Features and Char embedding layer
This project use dataset download from https://github.com/kamalkraj/BERT-NER data dir. Because the edit is simple, only release two jupyter notebooks for record.
By add Char embedding layer, The model accuracy improve from average 70% to 80% training from scratch.
Install TensorFlow 1 and requirements according to https://github.com/Determined22/zh-NER-TF
- Download Data from https://github.com/kamalkraj/BERT-NER/tree/dev/data
- Generate features like follows
-DOCSTART- -X- -X- O
EU NNP B-NP B-ORG
rejects VBZ B-VP O
German JJ B-NP B-MISC
call NN I-NP O
to TO B-VP O
boycott VB I-VP O
British JJ B-NP B-MISC
lamb NN I-NP O
. . O O
Peter NNP B-NP B-PER
Blackburn NNP I-NP I-PER
BRUSSELS NNP B-NP B-LOC
1996-08-22 CD I-NP O
1. Data Process and Network Train
2. Model Validation and conclusion decode
Distributed under the MIT License. See LICENSE
for more information.
svjack - [email protected]
Project Link: https://github.com/svjack/Bi-LSTM-CHAR-NER