Soft Well-Formed Semantic Parsing with Score-Based Selection

Result code in 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>

Result on the web

<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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Result language

angličtina

Original language name

Soft Well-Formed Semantic Parsing with Score-Based Selection

Original language description

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.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

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

Project

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Continuities

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Publication year

2024

Confidentiality

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

Article name in the collection

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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Number of pages

7

Pages from-to

15037-15043

Publisher name

European Language Resources Association (ELRA)

Place of publication

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Event location

Torino, Italia

Event date

Jan 1, 2025

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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