ASoleimaniB/NLQuAD
NLQuAD: A Non-Factoid Long Question Answering Data Set. To be published at EACL2021
This project offers a specialized dataset for training and evaluating question-answering systems. It takes BBC news articles as input and provides long, non-factoid questions derived from sub-headings, along with their corresponding body paragraphs as answers. Data scientists and researchers in natural language processing would use this to develop and benchmark models capable of understanding and extracting comprehensive answers from lengthy texts.
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Use this if you are a researcher or data scientist developing question-answering models and need a challenging dataset focused on extracting long, descriptive answers from news articles.
Not ideal if you are looking for a pre-built tool to answer questions from documents, or if your primary need is for short, fact-based answers.
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Python
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May 18, 2021
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