Machine Learning Approach for Pronominal Anaphora Resolution Based on Linguistic and Computational Features

Department

Civil Engineering

Document Type

Article

Publication Title

International Journal of Applied Mathematics and Machine Learning

ISSN

2394-2258

Volume

5

Issue

1

DOI

10.18642/ijamml_7100121700

First Page

81

Last Page

98

Publication Date

9-1-2016

Abstract

Anaphora resolution is the problem of resolving references of pronouns to antecedents (previously mentioned noun phrases) in text documents. It is a fundamental preprocessing step in text understanding (semantic) applications, including dialogue and story understanding, document summarization, information extraction, machine translation, and recognizing entailment relations in text. We propose a set of computational and linguistic features to resolve the pronominal anaphora in text documents for a machine learning approach. The system was evaluated on the BBN Pronoun Coreference and Entity Type Corpus, and an F-measure of 89% was obtained. The system was also tested on different genre of document and the performance is compared with the result of the annotated corpus.

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