Review of coreference resolution in English and Persian

• URL: http://arxiv.org/abs/2211.04428v1
• Date: Tue, 8 Nov 2022 18:14:09 GMT
• Title: Review of coreference resolution in English and Persian
• Authors: Hassan Haji Mohammadi, Alireza Talebpour, Ahmad Mahmoudi Aznaveh, Samaneh Yazdani
• Abstract summary: Coreference resolution (CR) is one of the most challenging areas of natural language processing. This article reviews the existing corpora and evaluation metrics in this field. Then, an overview of the coreference algorithms, from rule-based methods to the latest deep learning techniques are provided.
• Score: 5.419608513284392
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Coreference resolution (CR) is one of the most challenging areas of natural language processing. This task seeks to identify all textual references to the same real-world entity. Research in this field is divided into coreference resolution and anaphora resolution. Due to its application in textual comprehension and its utility in other tasks such as information extraction systems, document summarization, and machine translation, this field has attracted considerable interest. Consequently, it has a significant effect on the quality of these systems. This article reviews the existing corpora and evaluation metrics in this field. Then, an overview of the coreference algorithms, from rule-based methods to the latest deep learning techniques, is provided. Finally, coreference resolution and pronoun resolution systems in Persian are investigated.

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