SubjQA: A Dataset for Subjectivity and Review Comprehension

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  • SUBJQA

    Final published version, 1.32 MB, PDF document

Subjectivity is the expression of internal opinions or beliefs which cannot be objectively observed or verified, and has been shown to be important for sentiment analysis and word-sense disambiguation. Furthermore, subjectivity is an important aspect of user-generated data. In spite of this, subjectivity has not been investigated in contexts where such data is widespread, such as in question answering (QA). We develop a new dataset which allows us to investigate this relationship. We find that subjectivity is an important feature in the case of QA, albeit with more intricate interactions between subjectivity and QA performance than found in previous work on sentiment analysis. For instance, a subjective question may or may not be associated with a subjective answer. We release an English QA dataset (SubjQA) based on customer reviews, containing subjectivity annotations for questions and answer spans across 6 domains.
Original languageEnglish
Title of host publicationSUBJQA: A Dataset for Subjectivity and Review Comprehension
PublisherAssociation for Computational Linguistics
Publication date2020
Pages5480-5494
DOIs
Publication statusPublished - 2020
EventThe 2020 Conference on Empirical Methods in Natural Language Processing - online
Duration: 16 Nov 202020 Nov 2020
http://2020.emnlp.org

Conference

ConferenceThe 2020 Conference on Empirical Methods in Natural Language Processing
Locationonline
Periode16/11/202020/11/2020
Internetadresse

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