Anaphora and coreference resolution: A review

被引:75
|
作者
Sukthanker, Rhea [1 ]
Poria, Soujanya [2 ]
Cambria, Erik [3 ]
Thirunavukarasu, Ramkumar [4 ]
机构
[1] Swiss Fed Inst Technol, Dept Comp Sci, Zurich, Switzerland
[2] SUTD, Informat Syst Technol & Design, Singapore, Singapore
[3] Nanyang Technol Univ, Sch Comp Sci & Engn, Singapore, Singapore
[4] VIT Univ, Sch Informat Technol & Engn, Vellore, Tamil Nadu, India
关键词
Coreference resolution; Anaphora resolution; Natural language processing; Sentiment analysis; Deep learning; SENTIMENT ANALYSIS; CORPUS; FRAMEWORK;
D O I
10.1016/j.inffus.2020.01.010
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Coreference resolution aims at resolving repeated references to an object in a document and forms a core component of natural language processing (NLP) research. When used as a component in the processing pipeline of other NLP fields like machine translation, sentiment analysis, paraphrase detection, and summarization, coreference resolution has a potential to highly improve accuracy. A direction of research closely related to coreference resolution is anaphora resolution. Existing literature is often ambiguous in its usage of these terms and often uses them interchangeably. Through this review article, we clarify the scope of these two tasks. We also carry out a detailed analysis of the datasets, evaluation metrics and research methods that have been adopted to tackle these NLP problems. This survey is motivated by the aim of providing readers with a clear understanding of what constitutes these two tasks in NLP research and their related issues.
引用
收藏
页码:139 / 162
页数:24
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