Automatic Extraction of Clausal Embedding Based on Large-Scale English Text Data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3AWDMXHBER" target="_blank" >RIV/00216208:11320/26:WDMXHBER - isvavai.cz</a>

Výsledek na webu

<a href="https://arxiv.org/abs/2506.14064" target="_blank" >https://arxiv.org/abs/2506.14064</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.48550/arXiv.2506.14064" target="_blank" >10.48550/arXiv.2506.14064</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Automatic Extraction of Clausal Embedding Based on Large-Scale English Text Data

Popis výsledku v původním jazyce

For linguists, embedded clauses have been of special interest because of their intricate distribution of syntactic and semantic features. Yet, current research relies on schematically created language examples to investigate these constructions, missing out on statistical information and naturally-occurring examples that can be gained from large language corpora. Thus, we present a methodological approach for detecting and annotating naturally-occurring examples of English embedded clauses in large-scale text data using constituency parsing and a set of parsing heuristics. Our tool has been evaluated on our dataset Golden Embedded Clause Set (GECS), which includes hand-annotated examples of naturally-occurring English embedded clause sentences. Finally, we present a large-scale dataset of naturally-occurring English embedded clauses which we have extracted from the open-source corpus Dolma using our extraction tool.

Název v anglickém jazyce

Automatic Extraction of Clausal Embedding Based on Large-Scale English Text Data

Popis výsledku anglicky

For linguists, embedded clauses have been of special interest because of their intricate distribution of syntactic and semantic features. Yet, current research relies on schematically created language examples to investigate these constructions, missing out on statistical information and naturally-occurring examples that can be gained from large language corpora. Thus, we present a methodological approach for detecting and annotating naturally-occurring examples of English embedded clauses in large-scale text data using constituency parsing and a set of parsing heuristics. Our tool has been evaluated on our dataset Golden Embedded Clause Set (GECS), which includes hand-annotated examples of naturally-occurring English embedded clause sentences. Finally, we present a large-scale dataset of naturally-occurring English embedded clauses which we have extracted from the open-source corpus Dolma using our extraction tool.

Druh

J_ost - Ostatní články v recenzovaných periodicích

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

2025

Kód důvěrnosti údajů

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

Název periodika

arXiv preprint arXiv:2506.14064

ISSN

2331-8422

e-ISSN

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Svazek periodika

2025

Číslo periodika v rámci svazku

2025

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

11

Strana od-do

1-11

Kód UT WoS článku

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EID výsledku v databázi Scopus

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