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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16367
Title: Anaphora Resolution from Social Media Text
Authors: Sharma, Yashvardhan
Keywords: Computer Science
Co-reference Resolution
Anaphora Resolution
Natural Language Processing (NLP)
Neural Co-reference
Issue Date: 2022
Publisher: CEUR-WS
Abstract: Anaphora resolution for social media texts is essential yet difficult task for text understanding. An important characteristic of anaphora is that it creates a connection between the antecedent and the anaphor buried in the anaphoric sentence. This paper outlines the methods used to locate anaphora and their antecedents in a particular text. The text is a social media tweet for the SocAnaRes-IL 2022 challenge that was part of FIRE 2022. The proposed model uses a Neural Co-reference Network for the anaphora resolution
URI: https://ceur-ws.org/Vol-3395/T3-2.pdf
http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16367
Appears in Collections:Department of Computer Science and Information Systems

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