Conversational Question Answering

Natural Language Processing
Mar 2019

CoQA: A Conversational Question Answering Challenge

Mar 2019

The goal of the CoQA (Conversational Question Answering) challenge is to measure the ability of machines to understand a text passage and answer a series of interconnected questions that appear in a conversation.

CoQA challenge comes with a dataset which contains 127,000+ questions with answers collected from 8000+ conversations. Each conversation is collected by pairing two crowdworkers to chat about a passage in the form of questions and answers. The unique features of CoQA include 1) the questions are conversational; 2) the answers can be free-form text; 3) each answer also comes with an evidence subsequence highlighted in the passage; and 4) the passages are collected from seven diverse domains. CoQA has a lot of challenging phenomena not present in existing reading comprehension datasets, e.g., coreference and pragmatic reasoning.

Reference

Transactions of the Association for Computational Linguistics (TACL 2019)

Data sets

Linked Profiles