Soft Well-Formed Semantic Parsing with Score-Based Selection

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3APVYKCQ9D" target="_blank" >RIV/00216208:11320/25:PVYKCQ9D - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195907351&partnerID=40&md5=69a65feaccdc40310a5f6508a1b175cc" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195907351&partnerID=40&md5=69a65feaccdc40310a5f6508a1b175cc</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Soft Well-Formed Semantic Parsing with Score-Based Selection

Popis výsledku v původním jazyce

Semantic parsing is the task of translating natural language into a structured, formal semantic representation that can be interpreted by machines. These semantic representations are organized with complex structures. While various models have been developed for semantic parsing, there has been limited focus on generating semantic representations with well-formed structures. In this study, we introduce a score-based method to select well-formed outputs from candidates generated by beam search algorithms. Our experiments focus on parsing texts into discourse representation structures, which are innovative semantic representations designed to capture the meaning of texts with arbitrary lengths across languages. Our experimental results demonstrate that models utilizing the proposed method can reduce the number of ill-formed outputs and improve F1 scores in English. Furthermore, our final model achieves significant improvements in German, Italian and Dutch zero-shot DRS parsing by effectively preventing ill-formed outputs. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

Název v anglickém jazyce

Soft Well-Formed Semantic Parsing with Score-Based Selection

Popis výsledku anglicky

Semantic parsing is the task of translating natural language into a structured, formal semantic representation that can be interpreted by machines. These semantic representations are organized with complex structures. While various models have been developed for semantic parsing, there has been limited focus on generating semantic representations with well-formed structures. In this study, we introduce a score-based method to select well-formed outputs from candidates generated by beam search algorithms. Our experiments focus on parsing texts into discourse representation structures, which are innovative semantic representations designed to capture the meaning of texts with arbitrary lengths across languages. Our experimental results demonstrate that models utilizing the proposed method can reduce the number of ill-formed outputs and improve F1 scores in English. Furthermore, our final model achieves significant improvements in German, Italian and Dutch zero-shot DRS parsing by effectively preventing ill-formed outputs. © 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

7

Strana od-do

15037-15043

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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