Automatic Manipulation of Training Corpora to Make Parsers Accept Real-world Text

Kód výsledku v IS VaVaI

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

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195169614&partnerID=40&md5=e91a5062d5a98796f8cd59d78d29215a" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195169614&partnerID=40&md5=e91a5062d5a98796f8cd59d78d29215a</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Automatic Manipulation of Training Corpora to Make Parsers Accept Real-world Text

Popis výsledku v původním jazyce

This paper discusses how to build a practical syntactic analyzer, and addresses the distributional differences between existing corpora and actual documents in applications. As a case study we focus on noun phrases that are not headed by a main verb and sentences without punctuation at the end, which are rare in a number of Universal Dependencies corpora but frequently appear in the real-world use cases of syntactic parsers. We converted the training corpora so that their distribution is closer to that in realistic inputs, and obtained better scores both in general syntax benchmarking and a sentiment detection task, a typical application of dependency analysis. © European Language Resources Association: CC BY-NC 4.0.

Název v anglickém jazyce

Automatic Manipulation of Training Corpora to Make Parsers Accept Real-world Text

Popis výsledku anglicky

This paper discusses how to build a practical syntactic analyzer, and addresses the distributional differences between existing corpora and actual documents in applications. As a case study we focus on noun phrases that are not headed by a main verb and sentences without punctuation at the end, which are rare in a number of Universal Dependencies corpora but frequently appear in the real-world use cases of syntactic parsers. We converted the training corpora so that their distribution is closer to that in realistic inputs, and obtained better scores both in general syntax benchmarking and a sentiment detection task, a typical application of dependency analysis. © European Language Resources 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. Workshop Multiword Expressions Univers. Depend., MWE-UD LREC-COLING - Workshop Proc.

ISBN

978-249381420-3

ISSN

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e-ISSN

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Počet stran výsledku

10

Strana od-do

4-13

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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