Integrating Headedness Information into an Auto-generated Multilingual CCGbank for Improved Semantic Interpretation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AJIW28NPR" target="_blank" >RIV/00216208:11320/25:JIW28NPR - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195952366&partnerID=40&md5=91c67ce50ec9e861451479b55e5df193" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195952366&partnerID=40&md5=91c67ce50ec9e861451479b55e5df193</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Integrating Headedness Information into an Auto-generated Multilingual CCGbank for Improved Semantic Interpretation

Popis výsledku v původním jazyce

Previously, we introduced a method to generate a multilingual Combinatory Categorial Grammar (CCG) treebank by converting from the Universal Dependencies (UD). However, the method only produces bare CCG derivations without any accompanying semantic representations, which makes it difficult to obtain satisfactory analyses for constructions that involve non-local dependencies, such as control/raising or relative clauses, and limits the general applicability of the treebank. In this work, we present an algorithm that adds semantic representations to existing CCG derivations, in the form of predicate-argument structures. Through hand-crafted rules, we enhance each CCG category with headedness information, with which both local and non-local dependencies can be properly projected. This information is extracted from various sources, including UD, Enhanced UD, and proposition banks. Evaluation of our projected dependencies on the English PropBank and the Universal PropBank 2.0 shows that they can capture most of the semantic dependencies in the target corpora. Further error analysis measures the effectiveness of our algorithm for each language tested, and reveals several issues with the previous method and source data. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

Název v anglickém jazyce

Integrating Headedness Information into an Auto-generated Multilingual CCGbank for Improved Semantic Interpretation

Popis výsledku anglicky

Previously, we introduced a method to generate a multilingual Combinatory Categorial Grammar (CCG) treebank by converting from the Universal Dependencies (UD). However, the method only produces bare CCG derivations without any accompanying semantic representations, which makes it difficult to obtain satisfactory analyses for constructions that involve non-local dependencies, such as control/raising or relative clauses, and limits the general applicability of the treebank. In this work, we present an algorithm that adds semantic representations to existing CCG derivations, in the form of predicate-argument structures. Through hand-crafted rules, we enhance each CCG category with headedness information, with which both local and non-local dependencies can be properly projected. This information is extracted from various sources, including UD, Enhanced UD, and proposition banks. Evaluation of our projected dependencies on the English PropBank and the Universal PropBank 2.0 shows that they can capture most of the semantic dependencies in the target corpora. Further error analysis measures the effectiveness of our algorithm for each language tested, and reveals several issues with the previous method and source data. © 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

10

Strana od-do

9110-9119

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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