Annotating relation inference in context via question answering

Omer Levy; Ido Dagan

doi:10.18653/v1/p16-2041

Annotating relation inference in context via question answering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We present a new annotation method for collecting data on relation inference in context. We convert the inference task to one of simple factoid question answering, allowing us to easily scale up to 16,000 high-quality examples. Our method corrects a major bias in previous evaluations, making our dataset much more realistic.

Original language	English
Title of host publication	54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Short Papers
Publisher	Association for Computational Linguistics (ACL)
Pages	249-255
Number of pages	7
ISBN (Electronic)	9781510827592
DOIs	https://doi.org/10.18653/v1/p16-2041
State	Published - 2016
Externally published	Yes
Event	54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Berlin, Germany Duration: 7 Aug 2016 → 12 Aug 2016

Publication series

Name	54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Short Papers

Conference

Conference	54th Annual Meeting of the Association for Computational Linguistics, ACL 2016
Country/Territory	Germany
City	Berlin
Period	7/08/16 → 12/08/16

Access to Document

10.18653/v1/p16-2041

Cite this

Levy, O., & Dagan, I. (2016). Annotating relation inference in context via question answering. In 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Short Papers (pp. 249-255). (54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Short Papers). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/p16-2041

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title = "Annotating relation inference in context via question answering",

abstract = "We present a new annotation method for collecting data on relation inference in context. We convert the inference task to one of simple factoid question answering, allowing us to easily scale up to 16,000 high-quality examples. Our method corrects a major bias in previous evaluations, making our dataset much more realistic.",

author = "Omer Levy and Ido Dagan",

note = "Publisher Copyright: {\textcopyright} 2016 Association for Computational Linguistics.; 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 ; Conference date: 07-08-2016 Through 12-08-2016",

year = "2016",

doi = "10.18653/v1/p16-2041",

language = "אנגלית",

series = "54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Short Papers",

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pages = "249--255",

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Levy, O & Dagan, I 2016, Annotating relation inference in context via question answering. in 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Short Papers. 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Short Papers, Association for Computational Linguistics (ACL), pp. 249-255, 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016, Berlin, Germany, 7/08/16. https://doi.org/10.18653/v1/p16-2041

Annotating relation inference in context via question answering. / Levy, Omer; Dagan, Ido.
54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Short Papers. Association for Computational Linguistics (ACL), 2016. p. 249-255 (54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Short Papers).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Annotating relation inference in context via question answering

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