research-article

Chinese Zero Pronoun Resolution: A Chain-to-chain Approach

Authors:

Guodong ZhouAuthors Info & Claims

ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), Volume 19, Issue 1

Article No.: 2, Pages 1 - 21

https://doi.org/10.1145/3321129

Published: 05 June 2019 Publication History

Abstract

Chinese zero pronoun (ZP) resolution plays a critical role in discourse analysis. Different from traditional mention-to-mention approaches, this article proposes a chain-to-chain approach to improve the performance of ZP resolution in three aspects. First, consecutive ZPs are clustered into coreferential chains, each working as one independent anaphor as a whole. In this way, those ZPs far away from their overt antecedents can be bridged via other consecutive ZPs in the same coreferential chains and thus better resolved. Second, common noun phrases (NPs) are automatically grouped into coreferential chains using traditional approaches, each working as one independent antecedent candidate as a whole. That is, those NPs occurring in the same coreferential chain are viewed as one antecedent candidate as a whole, and ZP resolution is made between ZP coreferential chains and common NP coreferential chains. In this way, the performance can be much improved due to the effective reduction of the search space by pruning singletons and negative instances. Third and finally, additional features from ZP and common NP coreferential chains are employed to better represent anaphors and their antecedent candidates, respectively. Comprehensive experiments on the OntoNotes V5.0 corpus show that our chain-to-chain approach significantly outperforms the state-of-the-art mention-to-mention approaches. To our knowledge, this is the first work to resolve zero pronouns in a chain-to-chain way.

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Cited By

Li Y(2024)Cognitive and sociolectal constraints on the theme-recipient alternation: evidence from MandarinCorpus Linguistics and Linguistic Theory10.1515/cllt-2023-0127Online publication date: 5-Jul-2024
https://doi.org/10.1515/cllt-2023-0127
Mohd Noor NMohd Noah SAb Aziz M(2020)CLASSIFICATION OF SHORT POSSESSIVE CLITIC PRONOUN NYA IN MALAY TEXT TO SUPPORT ANAPHOR CANDIDATE DETERMINATIONJournal of Information and Communication Technology10.32890/jict2020.19.4.319:Number 4(513-532)Online publication date: 20-Aug-2020
https://doi.org/10.32890/jict2020.19.4.3
Ji DGao JFei HTeng CRen Y(2020)A deep neural network model for speakers coreference resolution in legal textsInformation Processing & Management10.1016/j.ipm.2020.10236557:6(102365)Online publication date: Nov-2020
https://doi.org/10.1016/j.ipm.2020.102365

Index Terms

Chinese Zero Pronoun Resolution: A Chain-to-chain Approach
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing

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Published In

cover image ACM Transactions on Asian and Low-Resource Language Information Processing

ACM Transactions on Asian and Low-Resource Language Information Processing Volume 19, Issue 1

January 2020

345 pages

ISSN:2375-4699

EISSN:2375-4702

DOI:10.1145/3338846

Editor:
Imed Zitouni
Microsoft, USA

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Copyright © 2019 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 June 2019

Accepted: 01 March 2019

Revised: 01 October 2018

Received: 01 December 2017

Published in TALLIP Volume 19, Issue 1

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National Science Fund for Distinguished Young Scholars of China
Artificial Intelligence Emergency Project
National Natural Science Foundation of China

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Cited By

Li Y(2024)Cognitive and sociolectal constraints on the theme-recipient alternation: evidence from MandarinCorpus Linguistics and Linguistic Theory10.1515/cllt-2023-0127Online publication date: 5-Jul-2024
https://doi.org/10.1515/cllt-2023-0127
Mohd Noor NMohd Noah SAb Aziz M(2020)CLASSIFICATION OF SHORT POSSESSIVE CLITIC PRONOUN NYA IN MALAY TEXT TO SUPPORT ANAPHOR CANDIDATE DETERMINATIONJournal of Information and Communication Technology10.32890/jict2020.19.4.319:Number 4(513-532)Online publication date: 20-Aug-2020
https://doi.org/10.32890/jict2020.19.4.3
Ji DGao JFei HTeng CRen Y(2020)A deep neural network model for speakers coreference resolution in legal textsInformation Processing & Management10.1016/j.ipm.2020.10236557:6(102365)Online publication date: Nov-2020
https://doi.org/10.1016/j.ipm.2020.102365

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