/propagate-selector

TensorFlow implementation of "Propagate-Selector: Detecting Supporting Sentences for Question Answering via Graph Neural Networks," LREC-20

Primary LanguagePythonMIT LicenseMIT

propagate-selector

This repository contains the source code & data corpus used in the following paper,

Propagate-Selector: Detecting Supporting Sentences for Question Answering via Graph Neural Networks, LREC-20, [paper]

[requirements]

tensorflow==1.10 (tested on cuda-9.2, cudnn-7.6.5)
python==3.5
tqdm==4.31.1
nltk==3.3
h5py==2.8.0
ujson==1.35

[download dataset & preprocessing]

  • download "HotpotQA" to ./data/raw/hotpot/
  • clone ELMo repository and download pretrained models
sh init_make_dataset.sh
  • processed file (train/dev.pkl)
  • [#samples, 4]
    • 0: question [#token]
    • 1: list (sentences) [#sentence, #token]
    • 2: index of first sentence of each passage [#sentence]
    • 3: label [#sentence]

[training Phase]

  • run reference script in "./model" folder
  • results will be displayed in console
  • results will be saved to "./model/TEST_run_result.txt" 
sh reference_script_train.sh

[hyper parameters]

  • major parameters : edit from "./model/reference_script_train.sh"
  • other parameters : edit from "./model/params.py"

[cite]

  • Please cite our paper, when you use our code | dataset | model

    @inproceedings{yoon2020propagate,
    title={Propagate-Selector: Detecting Supporting Sentences for Question Answering via Graph Neural Networks},
    author={Yoon, Seunghyun and Dernoncourt, Franck and Kim, Doo Soon and Bui, Trung and Jung, Kyomin},
    booktitle={Proceedings of The 12th Language Resources and Evaluation Conference},
    pages={5400--5407},
    year={2020}
    }