For more details, please refer to the paper: CharNER: Character-Level Named Entity Recognition
Access to full list of options by typing:
python exper.py --help
Example command:
python src/exper.py --activation bi-lstm --n_hidden 128 128 --drates .2 .5 .8 --lang cze
This command builds 2 Bidirectional LSTMs stacked of top of each other. Each forward and backward LSTM has 128 units. --drates (dropout rates) flag signals to use dropout. In this example, .2 dropout is applied to inputs (drops characters) and .5 & .8 dropouts are applied to the outputs of Bidirectional LSTMs. --lang flag dictates which folder to use under data/ directory
Each folder under data/ directory is composed of 3 files. train.bio, testa.bio, testb.bio are for training, development and test sets respectively. Each file contains word, tag pairs seperated with a tab. For examples, check out directories under data/.
pip install --upgrade https://github.com/Lasagne/Lasagne/archive/master.zip
pip install -r requirements.txt
- Onur Kuru
- Ozan Arkan Can
You can checkout the Keras version here.