Code and dataset for the EMNLP 2021 Finding paper "Can NLI Models Verify QA Systems’ Predictions?"

Overview

Can NLI Models Verify QA Systems' Predictions?

This repository contains the data and code for the following paper:

**Can NLI Models Verify QA Systems' Predictions? **
Jifan Chen, Eunsol Choi, Greg Durrett
EMNLP 2021 Findings

@article{chen2021can,
  title={Can NLI Models Verify QA Systems' Predictions?},
  author={Chen, Jifan and Choi, Eunsol and Durrett, Greg},
  journal={EMNLP Findings},
  year={2021}
}

Datasets

The NLI data converted from QA datasets through our pipeline described in the paper can be found here

Data Format

The data files are formatted as jsonlines; each example is described as the following:

Field Description
example_id Example ID
title_text Title of the Wikipedia page of the example, could be NONE
paragraph_text Paragraph containing the answer
question_text Question
answer_text Answer of the question
answer_sent_text Sentence containing the answer
decontext_answer_sent_text Decontextualized sentence containing the answer
question_statement_text Declarative version of the question by combining the answer
answer_scores Top 5 Answer score computed by the QA(BERT-joint) model
is_correct Whether the answer is correct
answer_sent_text Sentence containing the answer

Models

Getting started

git clone https://github.com/jifan-chen/QA-Verification-Via-NLI.git

Install the dependencies by running pip install -r requirements.txt

Question Converter & Decontextualizer

See README in seq2seq_converter.

NQ-NLI

coming soon

Contact

Please contact at [email protected] if you have any questions.

Owner
Jifan Chen
Stay young, stay simple
Jifan Chen
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