Pronominal anaphora resolution using salience score for Malayalam

S. Athira, T. S. Lekshmi, Rajeev R R, E. Sherly, P. C. Reghuraj
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引用次数: 4

Abstract

Anaphora resolution (AR) is the process of resolving references to an entity in the discourse. The paper presents an algorithm to identify the pronominals and its antecedents in the Malayalam text input. Anaphora resolution is achieved by employing a hybrid of statistical machine learning and rule based approaches. The system is implemented by exploiting the morphological richness of the language and it makes use of parts of speech tagging, subject-object identification and person-number-gender of the NPs. We outline a simple, efficient but a naive algorithm for anaphora resolution, which computes the salience value score for each antecedents. The system performance is evaluated with precision, recall measures which produced promising results. The anaphora resolution system itself can improve the performance of many NLP applications such as text summarisation, text categorisation and term extraction.
马拉雅拉姆语的代词回指消解
回指消解(AR)是对语篇中实体的指称进行消解的过程。本文提出了马来语文本输入中代词及其先行词的识别算法。通过采用统计机器学习和基于规则的方法的混合方法来实现回指解析。该系统利用语言的形态丰富性,利用词性标注、主客体识别、人称-数-性别识别等方法实现。我们概述了一种简单,高效但幼稚的回指解析算法,该算法计算每个先行词的显着值得分。系统的性能用精度、召回率等指标进行了评估,结果令人满意。回指解析系统本身可以提高许多自然语言处理应用的性能,如文本摘要、文本分类和术语提取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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