Computational Models of Anaphora

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AWGAM3D6S" target="_blank" >RIV/00216208:11320/25:WGAM3D6S - isvavai.cz</a>

Výsledek na webu

<a href="https://www.annualreviews.org/content/journals/10.1146/annurev-linguistics-031120-111653" target="_blank" >https://www.annualreviews.org/content/journals/10.1146/annurev-linguistics-031120-111653</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1146/annurev-linguistics-031120-111653" target="_blank" >10.1146/annurev-linguistics-031120-111653</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Computational Models of Anaphora

Popis výsledku v původním jazyce

Interpreting anaphoric references is a fundamental aspect of our language competence that has long attracted the attention of computational linguists. The appearance of ever-larger anaphorically annotated data sets covering more and more anaphoric phenomena in ever-greater detail has spurred the development of increasingly more sophisticated computational models; as a result, the most recent state-of-the-art neural models are able to achieve impressive performance by leveraging linguistic, lexical, discourse, and encyclopedic information. This article provides a thorough survey of anaphora resolution (coreference) throughout this development, reviewing the available data sets and covering both the preneural history of the field and—in more detail—current neural models, including research on less-studied aspects of anaphoric interpretation such as bridging reference resolution and discourse deixis interpretation.

Název v anglickém jazyce

Computational Models of Anaphora

Popis výsledku anglicky

Interpreting anaphoric references is a fundamental aspect of our language competence that has long attracted the attention of computational linguists. The appearance of ever-larger anaphorically annotated data sets covering more and more anaphoric phenomena in ever-greater detail has spurred the development of increasingly more sophisticated computational models; as a result, the most recent state-of-the-art neural models are able to achieve impressive performance by leveraging linguistic, lexical, discourse, and encyclopedic information. This article provides a thorough survey of anaphora resolution (coreference) throughout this development, reviewing the available data sets and covering both the preneural history of the field and—in more detail—current neural models, including research on less-studied aspects of anaphoric interpretation such as bridging reference resolution and discourse deixis interpretation.

Druh

J_ost - Ostatní články v recenzovaných periodicích

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

—

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Annual Review of Linguistics

ISSN

2333-9683

e-ISSN

2333-9691

Svazek periodika

9

Číslo periodika v rámci svazku

Volume 9, 2023

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

27

Strana od-do

561-587

Kód UT WoS článku

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EID výsledku v databázi Scopus

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