LCGbank: A Corpus of Syntactic Analyses Based on Proof Nets

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A8NDFGWZI" target="_blank" >RIV/00216208:11320/25:8NDFGWZI - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195890953&partnerID=40&md5=0b98a9ed129e0c4e4be4c415474991ae" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195890953&partnerID=40&md5=0b98a9ed129e0c4e4be4c415474991ae</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

LCGbank: A Corpus of Syntactic Analyses Based on Proof Nets

Popis výsledku v původním jazyce

In syntactic parsing, proof nets are graphical structures that have the advantageous property of invariance to spurious ambiguities. Semantically-equivalent derivations correspond to a single proof net. Recent years have seen fresh interest in statistical syntactic parsing with proof nets, including the development of methods based on neural networks. However, training of statistical parsers requires corpora that provide ground-truth syntactic analyses. Unfortunately, there has been a paucity of corpora in formalisms for which proof nets are applicable, such as Lambek categorial grammar (lcg), a formalism related to combinatory categorial grammar (ccg). To address this, we leverage CCGbank and the relationship between lcg and ccg to develop LCGbank, an English-language corpus of syntactic analyses based on lcg proof nets. In contrast to CCGbank, LCGbank eschews type-changing and uses only categorial rules; the syntactic analyses thus provide fully compositional semantics, exploiting the transparency between syntax and semantics that so characterizes categorial grammars. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

Název v anglickém jazyce

LCGbank: A Corpus of Syntactic Analyses Based on Proof Nets

Popis výsledku anglicky

In syntactic parsing, proof nets are graphical structures that have the advantageous property of invariance to spurious ambiguities. Semantically-equivalent derivations correspond to a single proof net. Recent years have seen fresh interest in statistical syntactic parsing with proof nets, including the development of methods based on neural networks. However, training of statistical parsers requires corpora that provide ground-truth syntactic analyses. Unfortunately, there has been a paucity of corpora in formalisms for which proof nets are applicable, such as Lambek categorial grammar (lcg), a formalism related to combinatory categorial grammar (ccg). To address this, we leverage CCGbank and the relationship between lcg and ccg to develop LCGbank, an English-language corpus of syntactic analyses based on lcg proof nets. In contrast to CCGbank, LCGbank eschews type-changing and uses only categorial rules; the syntactic analyses thus provide fully compositional semantics, exploiting the transparency between syntax and semantics that so characterizes categorial grammars. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

Druh

D - Stať ve sborníku

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

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Návaznosti

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Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název statě ve sborníku

Jt. Int. Conf. Comput. Linguist., Lang. Resour. Eval., LREC-COLING - Main Conf. Proc.

ISBN

978-249381410-4

ISSN

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e-ISSN

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Počet stran výsledku

12

Strana od-do

10225-10236

Název nakladatele

European Language Resources Association (ELRA)

Místo vydání

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Místo konání akce

Torino, Italia

Datum konání akce

1. 1. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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