Att-ChemdNER

This repo contains the source code and dataset for the following paper:

Ling Luo, Zhihao Yang, Pei Yang, Yin Zhang, Lei Wang, Hongfei Lin, Jian Wang. An Attention-based BiLSTM-CRF Approach to Document-level Chemical Named Entity Recognition. Bioinformatics, 2017.

Dependency package

Att-ChemdNER uses the following dependencies:

Content

data
- CHENDNER corpus
- CDR corpus
models
- The basic BiLSTM-CRF model
- The Att-BiLSTM-CRF model
- The 50-dimensional word embedding
src
- backend
- evaluation: evaluate result of NER task
- activations.py: activation functions
- initializations.py
- loader.py: load the data set
- model.py: build the model
- nn.py: the layers of the network architecture
- optimizaiton.py: optimization method
- utils.py
- train.py: train a basic BiLSTM-CRF model
- AttenTrain.py: train a Att-BiLSTM-CRF model
- tagger.py: tag the document using the BiLSTM-CRF model
- AttenTrain.py: tag the document using the Att-BiLSTM-CRF model

Train a basic BiLSTM-CRF model

To train a basic BiLSTM-CRF model, you need to provide the file of the training set, development set,testing set and word embedding model, and run the train.py script:

python train.py --train trainfile --dev devfile --test testfile --pre_emb word_embedding.model

Train a Att-BiLSTM-CRF model

To train our Att-BiLSTM-CRF model, you need to provide the file of the training set, development set,testing set and word embedding model, and run the AttenTrain.py script:

python AttenTrain.py --train trainfile --dev devfile --test testfile --pre_emb word_embedding.model

Tag the documents using the BiLSTM-CRF model

Recognize the chemical entities from the documents using the pretrained BiLSTM-CRF model, and you need to provide the pretrained model, inputfile and outputfile:

python tagger.py --model BiLSTM-CRF.model --input inputfile --output outputfile

The inputfile should contain one document by line, and they have to be tokenized.

Tag the documents using the Att-BiLSTM-CRF model

Recognize the chemical entities from the documents using the pretrained Att-BiLSTM-CRF model, and you need to provide the pretrained model, inputfile and outputfile:

python Atten_tagger.py --model Att-BiLSTM-CRF.model --input inputfile --output outputfile