Taggerflow

This repository contains the code for training the supertagging model from LSTM CCG Parsing at NAACL (Lewis et al., 2016).

Dependencies

Tensorflow (r0.11 or above)
https://www.tensorflow.org/versions/r0.11/get_started/os_setup.html#pip-installation

Training and Evaluation

python taggerflow.py grid.json
- Trains a supertagging model.
- Logs evaluation results.
- Writes checkpoints to the log directory.

Exporting to EasySRL

python taggerflow.py grid.json -c <checkpoint_path>
- Evaluates the checkpoint on the dev set as a sanity check.
- Exports the model information to a temporary directory.
- Prints the temporary directory with the exported model.
The temporary directory should contain graph.pb and various .txt files.
Download and extract http://lil.cs.washington.edu/resources/model_tritrain_finetune.tgz, which provides the correct file structure.
Remove the existing taggerflow directory and replace it with the temporary directory.

Running EasySRL

Clone the EasySRL repository: https://github.com/uwnlp/EasySRL.
Download http://lil.cs.washington.edu/resources/libtaggerflow.so and move it to the lib directory.
EasySRL will use the trained supertagger for parsing when given the modified model_tritrain_finetune directory.