Hybrid Approach to Pronominal Anaphora Resolution in English Newspaper Text

Full Text (PDF, 322KB), PP.56-64

Views: 0 Downloads: 0


Kalyani P. Kamune 1,* Avinash Agrawal 1

1. RKNEC, Department of Computer Science, Nagpur, 440013, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2015.02.08

Received: 5 Jul. 2014 / Revised: 7 Oct. 2014 / Accepted: 2 Nov. 2014 / Published: 8 Jan. 2015

Index Terms

Natural Language processing, Anaphora resolution, Discourse, Pronominal Resolution, Co-reference, Discourse Modeling, Artificial Intelligence


One of the challenges in natural language understanding is to determine which entities to be referred in the discourse and how they relate to each other. Anaphora resolution needs to be addressed in almost every application dealing with natural language such as language understanding and processing, dialogue system, system for machine translation, discourse modeling, information extraction. This paper represents a system that uses the combination of constraint-based and preferences-based architectures; each uses a different source of knowledge and proves effective on computational and theoretical basis, instead of using a monolithic architecture for anaphora resolution. This system identifies both inter-sentential and intra-sentential antecedents of “Third person pronoun anaphors” and “Pleonastic it”. This system uses Charniak Parser (parser05Aug16) as an associated tool, and it relays on the output generated by it. Salience measures derived from parse tree are used in order to find out accurate antecedents from the list of all potential antecedents. We have tested the system extensively on 'Reuters Newspaper corpus' and efficiency of the system is found to be 81.9%.

Cite This Paper

Kalyani P. Kamune, Avinash Agrawal, "Hybrid Approach to Pronominal Anaphora Resolution in English Newspaper Text", International Journal of Intelligent Systems and Applications(IJISA), vol.7, no.2, pp.56-64, 2015. DOI:10.5815/ijisa.2015.02.08


[1]Aarts Jan, Henk Barkema and Nelleke Oostdijk (1997), “The TOSCA-ICLE Tagset: Tagging Manual”, TOSCA Research Group for Corpus Linguistics.
[2]Baldwin, Breck (1997), “CogNIAC: high precision coreference with limited knowledge and linguistic resources”, Proceedings of the ACL'97/EACL'97 workshop on Operational factors in practical, robust anaphora resolution
[3]Cardie, Claire and Kiri Wagstaff (1999), “Noun Phrase Coreference as Clustering”, Proceedings of the Joint Conference on Empirical Methods in Natural Language Processing and Very Large Corpora.
[4]Chinatsu Aone and Scott William Bennett, “Evaluating Automated and Manual Acquisition of Anaphora Resolution Strategies”, International Workshop on Sharable Natural Language Resources (SNLR),2000
[5]Dagan, Ido and Alon Itai (1990), “Automatic processing of large corpora for the resolution of anaphora references”, Proceedings of the 13th International Conference on Computational Linguistics (COLING'90), Vol. III, 1-3, Helsinki, Finland.
[6]Denber, Michel (1998), “Automatic resolution of anaphora in English”, Technical report, Eastman Kodak Co.
[7]Mitkov and Ruslan, “Anaphora resolution in Natural Language Processing and Machine Translation”. Working paper. Saarbrücken: IAI, 1995a.
[8]Mitkov, Ruslan, "Factors in anaphora resolution: they are not the only things that matter. A case study based on two different approaches" Proceedings of the ACL'97/EACL'97 workshop on Operational factors in practical, robust anaphora resolution, 14-21. Madrid, Spain, 1997b.
[9]Mitkov, Ruslan and Catalina Barbu (2001), “Evaluation tool for rule-based anaphora resolution methods”, Proceedings of ACL'01, Toulouse, 2001.
[10]Mitkov, Ruslan, Richard Evans and Constantin Orasan (2002), “A new, fully automatic version of Mitkov's knowledge-poor pronoun resolution method”, In Proceedings of CICLing- 2000, Mexico City, Mexico.
[11]Shalom Lappin and Herbert J. Leass ,”An Algorithm for Pronominal Anaphora Resolution”, 1994
[12]Ruslan Mitkov, “ANAPHORA RESOLUTION: THE STATE OF THE ART”, International Conference on Mathematical Linguistics, 2008.