Title of article :
Mehr: A Persian Coreference Resolution Corpus
Author/Authors :
Haji Mohammadi ، Hassan Department of Computer Engineering - Islamic Azad University, North Tehran Branch , Talebpour ، Alireza Department of computer engineering - Shahid Beheshti University , Mahmoudi Aznaveh ، Ahamd Department of computer engineering - Shahid Beheshti University , Yazdani ، Samaneh Department of Computer Engineering - Islamic Azad University, North Tehran Branch
Abstract :
Coreference resolution is one of the essential tasks of natural languageprocessing. This task identifies all in-text expressions that refer to thesame entity in the real world. Coreference resolution is used in otherfields of natural language processing, such as information extraction,machine translation, and question-answering.This article presents a new coreference resolution corpus in Persiannamed Mehr corpus. The article’s primary goal is to develop a Persiancoreference corpus that resolves some of the previous Persian corpus’sshortcomings while maintaining a high inter-annotator agreement. Thiscorpus annotates coreference relations for noun phrases, namedentities, pronouns, and nested named entities. Two baseline pronounresolution systems are developed, and the results are reported. Thecorpus size includes 400 documents and about 170k tokens. Corpusannotation is done by WebAnno preprocessing tool.
Keywords :
Natural Language Processing , Mention , Anaphora resolution , Antecedent
Journal title :
Journal of Artificial Intelligence and Data Mining
Journal title :
Journal of Artificial Intelligence and Data Mining