Multilingual coreference resolution

Harabagiu, Sanda M.; Maiorano, Steven J.

doi:10.3115/974147.974167

Cited by 18 publications

(8 citation statements)

References 13 publications

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“…Grishina (2019) provides a comprehensive overview of annotation projection methods applied to coreference resolution specifically. The discussed studies range from experimenting with manual projection of coreference chains (Harabagiu and Maiorano, 2000) to fully relying on translationbased approaches (Ogrodniczuk, 2013). In most of the works, English has been used as a source language; however, projecting from multiple other languages at the same time has been shown to improve the quality of the projected annotations.…”

Section: Annotation Projectionmentioning

confidence: 99%

Silver Data for Coreference Resolution in Ukrainian: Translation, Alignment, and Projection

Kuchmiichuk

2023

Proceedings of the Second Ukrainian Natural Language Processing Workshop (UNLP)

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Low-resource languages continue to present challenges for current NLP methods, and multilingual NLP is gaining attention in the research community. One of the main issues is the lack of sufficient high-quality annotated data for low-resource languages. In this paper, we show how labeled data for high-resource languages such as English can be used in low-resource NLP. We present two silver datasets for coreference resolution in Ukrainian, adapted from existing English data by manual translation and machine translation in combination with automatic alignment and annotation projection. The code is made publicly available 1 .

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Section: Annotation Projectionmentioning

confidence: 99%

Silver Data for Coreference Resolution in Ukrainian: Translation, Alignment, and Projection

Kuchmiichuk

2023

Proceedings of the Second Ukrainian Natural Language Processing Workshop (UNLP)

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“…The importance of the information on this variation is known, as for instance, the CoNLL-2012 shared task on coreference resolution included multiple languages, modes and registers within OntoNotes (Recasens and Pradhan, 2016). Information on languagedriven variational mechanisms in coreference is valuable for multilingual coreference resolution systems (Rahman and Ng, 2012;Pradhan et al, 2012;Recasens et al, 2010;Harabagiu and Maiorano, 2000). Kübler and Zhekova (2016) describe difficulties and challenges of this task showing that many issues remain unsolved in multilingual coreference resolution.…”

Section: Introductionmentioning

confidence: 99%

Exploring Coreference Features in Heterogeneous Data

Lapshinova-Koltunski¹,

Kunz²

2020

Proceedings of the First Workshop on Computational Approaches to Discourse

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The present paper focuses on variation phenomena in coreference chains. We address the hypothesis that the degree of structural variation between chain elements depends on language-specific constraints and preferences and, even more, on the communicative situation of language production. We define coreference features that also include reference to abstract entities and events. These features are inspired through several sources -cognitive parameters, pragmatic factors and typological status. We pay attention to the distributions of these features in a dataset containing English and German texts of spoken and written discourse mode, which can be classified into seven different registers. We apply text classification and feature selection to find out how these variational dimensions (language, mode and register) impact on coreference features. Knowledge on the variation under analysis is valuable for contrastive linguistics, translation studies and multilingual natural language processing (NLP), e.g. machine translation or cross-lingual coreference resolution.

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“…French corpus [16], annotate anaphoric links in MUC. Few multilingual corpora are available like EnglishRomanian corpus [17], technical manual of English-French for co-referential link at the University of Wolverhampton.…”

Section: B Annotated Corpora For Coreference and Anaphoramentioning

confidence: 99%

Automation and Validation of Annotation for Hindi Anaphora Resolution

Singh¹,

Dutta²

2015

ijacsa

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Abstract-The process of labelling any language genre by which one can extract useful information is called annotation. This provides syntactic information about a word or a word phrase. In this paper, an effort has been made to provide the algorithm for semiautomatic annotation for Hindi text to cater anaphora resolution only. The study was conducted on twelve files of Ranchi Express available in EMILLE corpus. The corpus is originally tagged for demonstrative pronouns. The detection of the pronouns is supported by the incorporation of seven tags. However the semantic interpretation of the demonstrative pronoun is not supported in the original corpus. In this paper an effort has been made to automate the process of tagging as well as the handling of semantic information through addition tags. It was conducted on 1485 demonstrative pronouns. The average accuracy of precision, recall and F measure is 74, 71 and 72 respectively.

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Multilingual coreference resolution

Cited by 18 publications

References 13 publications

Silver Data for Coreference Resolution in Ukrainian: Translation, Alignment, and Projection

Silver Data for Coreference Resolution in Ukrainian: Translation, Alignment, and Projection

Exploring Coreference Features in Heterogeneous Data

Automation and Validation of Annotation for Hindi Anaphora Resolution

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