ritam-9 / sequence-tagging-ner

Keras Bi-LSTM-CRF for sequence tagging

Keras-BiLSTMCRF

Keras Implementation of the BiLSTM-CRF model as described in https://guillaumegenthial.github.io/.

For the PyTorch implementation (with ELMO) please refer to this link.

Usage

1. Requirements:
   a. Packages: Anaconda, TensorFlow, Keras
   b. Data: Train, valid and test datasets in CoNLL 2003 NER format.
   c. Glove 300B embeddings (optional)

2. Configure Settings:
   a. Change settings in model/config.py
   b. Main settings to change: File directories, model hyperparameters etc.

3. Build Data:
   a. Run build_data.py
   i. Builds embedding dictionary, text file of words, chars tags, as well as idx to word and idx to char mapping for the model to read

4. Train Model:
   a. Run train_keras.py

5. Test Model:
   a. Run evaluate_keras.py
   b. Evaluates on test set. Also accepts other arguments to predict on custom string