PIECER

Introduction

This project contains the main code to train and evaluate four base MRC models (QANet, BERT-base, BERT-large, RoBERTa-base) + PIECER.

Usage

For QANet + PIECER, run bash run_qanet.sh

For BERT-base + PIECER, run bash run_bert.sh

For BERT-large + PIECER, run bash run_bertl.sh

For RoBERTa-base + PIECER, run bash run_roberta.sh

Hyper-parameters can be manually set in each shell script.

Data

ReCoRD can be downloaded from its homepage or the SuperGLUE download link.

ConceptNet can be downloaded from its download link.

Our used data are totally oriented from these two sources. We will also release the preprocessing scripts and the preprocessed data later.

Citation

If you use this code for your research, please kindly cite our NLPCC-2022 paper:

@inproceedings{dai2022piecer,
  author    = {Damai Dai and
               Hua Zheng and
               Zhifang Sui and
               Baobao Chang},
  title     = {Plug-and-Play Module for Commonsense Reasoning in Machine Reading Comprehension},
  booktitle = {Proceedings of the 11th CCF International Conference on Natural Language Processing and Chinese Computing, {NLPCC} 2022, Guilin, China, September 22-25, 2022},
  year      = {2022},
}

Contact

Damai Dai: daidamai@pku.edu.cn