Slot-Gated Modeling for Joint Slot Filling and Intent Prediction

Reference

Main paper to be cited

@inproceedings{goo2018slot,
  title={Slot-Gated Modeling for Joint Slot Filling and Intent Prediction},
    author={Chih-Wen Goo and Guang Gao and Yun-Kai Hsu and Chih-Li Huo and Tsung-Chieh Chen and Keng-Wei Hsu and Yun-Nung Chen},
    booktitle={Proceedings of The 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},
    year={2018}
}

Data

split your data into text file(seq.in), slot file(seq.out) and intent file(label)
following is default setting used by train.py
./data/
 --train/
  --seq.in
  --seq.out
  --label
 --test/
  --seq.in
  --seq.out
  --label
 --valid/
  --seq.in
  --seq.out
  --label

Requirements

tensorflow 1.4
python 3.5

Usage

some sample usage

• run with 32 units and no patience for early stop
   python3 train.py --num_units=32 --patience=0

• disable early stop and use intent attention version
   python3 train.py --no_early_stop --model_type=intent_only

• use "python3 train.py -h" for all avaliable parameter settings