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Anaphora and coreference resolution: A review [PDF]

open access: yesInformation Fusion, 2020
Entity resolution aims at resolving repeated references to an entity in a document and forms a core component of natural language processing (NLP) research. This field possesses immense potential to improve the performance of other NLP fields like machine translation, sentiment analysis, paraphrase detection, summarization, etc.
Soujanya Poria   +2 more
exaly   +4 more sources
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A Survey of Chinese Anaphora Resolution

Lecture Notes in Computer Science, 2021
Chinese anaphora resolution technology has been widely used in many natural language processing tasks, such as machine translation, information extraction and automatic text summarization. In this paper, we first introduce the resources for anaphora resolution, and then present the existing works on Chinese noun phrase resolution based on machine ...
Junsheng Zhou   +2 more
exaly   +2 more sources

Anaphora resolution with pointer networks

Pattern Recognition Letters, 2017
Abstract Anaphora resolution is a fundamental problem in natural language processing. In this paper, we cast an anaphora resolution problem to a statistical pointing problem. To address the problem, we use the Pointer Networks model for a neural sequential anaphora pointing architecture.
Changki Lee, Sangkeun Jung
exaly   +2 more sources

Anaphora Resolution

2014
Khadiga Mahmoud Seddik, Ali Farghaly
exaly   +2 more sources

The Development of Anaphora Resolution in Spanish

Journal of Psycholinguistic Research, 2019
The present study focuses on the development of Spanish pronominal processing. We investigate whether the pronoun interpretation problem (i.e., reflexive pronouns comprehension is resolved at an earlier age than that of personal pronouns, also known as the Delay of the Principle B Effect), which has been documented in other languages, also occurs in ...
Isabel R. Rodríguez-Ortiz   +3 more
openaire   +2 more sources

Multilingual Anaphora Resolution

Machine Translation, 1999
This paper presents a multilingual robust, knowledge-poor approach to resolving pronouns in technical manuals. This approach is a modification of the practical approach (Mitkov 1998a) and operates on texts pre-processed by a part-of-speech tagger. Input is checked against agreement and a number of antecedent indicators.
openaire   +1 more source

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