A Crowdsourced Corpus of Multiple Judgments and Disagreement on Anaphoric Interpretation

URN to cite this document:: urn:nbn:de:bvb:355-epub-434200
DOI to cite this document:: 10.5283/epub.43420

Poesio, Massimo ; Chamberlain, Jon ; Paun, Silviu ; Yu, Juntao ; Uma, Alexandra ; Kruschwitz, Udo

Preview

License: Creative Commons Attribution 4.0
PDF - Published Version
(190kB)

Date of publication of this fulltext: 29 Jun 2020 13:34

Alternative links to fulltext:Publisher

Details

Item type:	Conference or workshop item (UNSPECIFIED)
Title of Book:	Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
Publisher:	Association for Computational Linguistics
Place of Publication:	Minneapolis, Minnesota
Page Range:	pp. 1778-1789
Date:	June 2019
Institutions:	Languages and Literatures > Institut für Information und Medien, Sprache und Kultur (I:IMSK) > Lehrstuhl für Informationswissenschaft (Prof. Dr. Udo Kruschwitz) Informatics and Data Science > Department Human-Centered Computing > Lehrstuhl für Informationswissenschaft (Prof. Dr. Udo Kruschwitz)
Dewey Decimal Classification:	000 Computer science, information & general works > 020 Library & information sciences
Status:	Published
Refereed:	Yes, this version has been refereed
Created at the University of Regensburg:	Yes
Item ID:	43420

Preview

Export bibliographical data

Abstract

We present a corpus of anaphoric information (coreference) crowdsourced through a game-with-a-purpose. The corpus, containing annotations for about 108,000 markables, is one of the largest corpora for coreference for English, and one of the largest crowdsourced NLP corpora, but its main feature is the large number of judgments per markable: 20 on average, and over 2.2M in total. This ...