Skip to content

Code for ACL 2019 paper "Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphs"

License

Notifications You must be signed in to change notification settings

JD-AI-Research-Silicon-Valley/HDEGraph

Repository files navigation

HDEGraph

Code for ACL 2019 paper "Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphs"

Based on PyTorch

Overview

Evaluation code for HDEGraph on WikiHop leaderboad with pretrained models.

Installation

  1. git clone

  2. Install PyTorch. The code has been tested with PyTorch >= 1.0

  3. Install the requirements

  4. Download pretrained models. Put zip file into the same folder with run.py, and unzip it.

Running

Run

python run.py input_file output_file

input_file can be WikiHop dev file or other data sets organized in the same format with WikiHop.

output_file is the file where predictions locate at

Citation

@inproceedings{tu2019multi,
  title={Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphs},
  author={Tu, Ming and Wang, Guangtao and Huang, Jing and Tang, Yun and He, Xiaodong and Zhou, Bowen},
  booktitle={Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics},
  pages={2704--2713},
  year={2019}
}

About

Code for ACL 2019 paper "Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphs"

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages