文章基本信息

标题：A Comparative Mention-Pair Models for Coreference Resolution in DARI Language for Information Extraction
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作者：Ghezal Ahmad Jan Zia ; Ahmad Zia Sharifi ; Fazl Ahmad Amini 等
期刊名称：Computer Science & Information Technology
电子版ISSN：2231-5403
出版年度：2019
卷号：9
期号：7
页码：1-14
DOI：10.5121/csit.2019.90708
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Coreference resolution plays an important role in Information Extraction.This paper covers the investigation of two strategies based on a mention-pair resolver using Decision Tree classifier on structured and unstructured dataset, targeting coreference resolution in Dari language. Strategies are (1) training separate models which is specialized in particular categories (e.g., lexical, syntactic and semantic) and types of mentions (e.g. pronouns, proper nouns) and (2) using a structured dataset on a machine learning library that is designed to classify numerical values. Moreover, these modifications and comparative models describe a contribution of comprehensive factors involved in the resolution of texts. Specifically, we developed the first Dari corpus (’DariCoref’) based on OntoNotes and WikiCoref scheme. Both strategies are produced f-score of state-of-the-art.