ChEMU-Ref: A corpus for modeling anaphora resolution in the chemical domain

Biaoyan Fang, Christian Druckenbrodt, Saber A. Akhondi, Jiayuan He, Timothy Baldwin, Karin Verspoor

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

27 Scopus citations

Abstract

Chemical patents contain rich coreference and bridging links, which are the target of this research. Specially, we introduce a novel annotation scheme, based on which we create the ChEMU-Ref dataset from reaction description snippets in English-language chemical patents. We propose a neural approach to anaphora resolution, which we show to achieve strong results, especially when jointly trained over coreference and bridging links.

Original languageEnglish
Title of host publicationEACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference
PublisherAssociation for Computational Linguistics (ACL)
Pages1362-1375
Number of pages14
ISBN (Electronic)9781954085022
StatePublished - 2021
Externally publishedYes
Event16th Conference of the European Chapter of the Associationfor Computational Linguistics, EACL 2021 - Virtual, Online
Duration: Apr 19 2021Apr 23 2021

Publication series

NameEACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference

Conference

Conference16th Conference of the European Chapter of the Associationfor Computational Linguistics, EACL 2021
CityVirtual, Online
Period04/19/2104/23/21

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