Distinguishing the Types of Coordinated Verbs with a Shared Argument by means of New ZeugBERT Language Model and ZeugmaDataset

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14210%2F22%3A00126225" target="_blank" >RIV/00216224:14210/22:00126225 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.3233/SSW220022" target="_blank" >http://dx.doi.org/10.3233/SSW220022</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3233/SSW220022" target="_blank" >10.3233/SSW220022</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Distinguishing the Types of Coordinated Verbs with a Shared Argument by means of New ZeugBERT Language Model and ZeugmaDataset

Popis výsledku v původním jazyce

Sentences where two verbs share a single argument represent a complex and highly ambiguous syntactic phenomenon. The argument sharing relations must be considered during the detection process from both a syntactic and semantic perspective. Such expressions can represent ungrammatical constructions, denoted as zeugma, or idiomatic elliptical phrase combinations. Rule-based classification methods prove ineffective because of the necessity to reflect meaning relations of the analyzed sentence constituents. This paper presents the development and evaluation of ZeugBERT, a language model tuned for the sentence classification task using a pre-trained Czech transformer model for language representation. The model was trained with a newly prepared dataset, which is also published with this paper, of 7,849 Czech sentences to classify Czech syntactic structures containing coordinated verbs that share a valency argument (or an optional adjunct) in the context of coordination. ZeugBERT here reaches $88,%$ of test set accuracy. The text describes the process of the new dataset creation and annotation, and it offers a detailed error analysis of the developed classification model.

Název v anglickém jazyce

Distinguishing the Types of Coordinated Verbs with a Shared Argument by means of New ZeugBERT Language Model and ZeugmaDataset

Popis výsledku anglicky

Sentences where two verbs share a single argument represent a complex and highly ambiguous syntactic phenomenon. The argument sharing relations must be considered during the detection process from both a syntactic and semantic perspective. Such expressions can represent ungrammatical constructions, denoted as zeugma, or idiomatic elliptical phrase combinations. Rule-based classification methods prove ineffective because of the necessity to reflect meaning relations of the analyzed sentence constituents. This paper presents the development and evaluation of ZeugBERT, a language model tuned for the sentence classification task using a pre-trained Czech transformer model for language representation. The model was trained with a newly prepared dataset, which is also published with this paper, of 7,849 Czech sentences to classify Czech syntactic structures containing coordinated verbs that share a valency argument (or an optional adjunct) in the context of coordination. ZeugBERT here reaches $88,%$ of test set accuracy. The text describes the process of the new dataset creation and annotation, and it offers a detailed error analysis of the developed classification model.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

60203 - Linguistics

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název statě ve sborníku

Towards a Knowledge-Aware AI : SEMANTiCS 2022 — Proceedings of the 18th International Conference on Semantic Systems, 13-15 September 2022, Vienna, Austria

ISBN

9781643683201

ISSN

—

e-ISSN

—

Počet stran výsledku

13

Strana od-do

206-218

Název nakladatele

IOS Press

Místo vydání

Amsterdam

Místo konání akce

Vienna, Austria

Datum konání akce

1. 1. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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