Open-Retrieval Conversational Question Answering (ORConvQA) Dataset
Created by Qu et al. at 2020, the Open-Retrieval Conversational Question Answering (ORConvQA) Dataset enhances QuAC by adapting it to an open retrieval setting. It is an aggregation of 3 existing datasets: (1) the QuAC dataset that offers information-seeking conversations, (2) the CANARD dataset that consists of context-independent rewrites of QuAC questions, and (3) the Wikipedia corpus that serves as the knowledge source of answering questions., in English language. Containing 5,644 in Text file format.
Dataset Sources
Here you can download the Open-Retrieval Conversational Question Answering (ORConvQA) dataset in Text format.
Download Open-Retrieval Conversational Question Answering (ORConvQA) dataset Text files
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Paper
Read full original Open-Retrieval Conversational Question Answering (ORConvQA) paper.
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