Lemmatization of Czech and Croatian Noun Clusters for Terminology Extraction

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F25%3A00142890" target="_blank" >RIV/00216224:14330/25:00142890 - isvavai.cz</a>

Výsledek na webu

<a href="https://nlp.fi.muni.cz/raslan/2025/" target="_blank" >https://nlp.fi.muni.cz/raslan/2025/</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Lemmatization of Czech and Croatian Noun Clusters for Terminology Extraction

Popis výsledku v původním jazyce

During terminology extraction, terms discovered in corpora are presented in their canonical form. Lemmatization of multi-word terms consisting of noun clusters can be ambiguous due to the lack of information on their internal structure. In this paper, we show that grammatical case alone is often not sufficient for the construction of canonical forms of noun clusters. We focus on two-noun clusters in the genitive, which are the most frequent type with ambiguous parsing. Based on corpus research, we design rules that make use of multiple morphological categories to improve the lemmatization of noun clusters found in Czech and Croatian corpora. In addition to case, we also take note of gender, animacy, and whether the noun is a proper noun. The improvements lead to more accurate and more unified forms of the terms produced during terminology extraction for these two languages in Sketch Engine.

Název v anglickém jazyce

Lemmatization of Czech and Croatian Noun Clusters for Terminology Extraction

Popis výsledku anglicky

During terminology extraction, terms discovered in corpora are presented in their canonical form. Lemmatization of multi-word terms consisting of noun clusters can be ambiguous due to the lack of information on their internal structure. In this paper, we show that grammatical case alone is often not sufficient for the construction of canonical forms of noun clusters. We focus on two-noun clusters in the genitive, which are the most frequent type with ambiguous parsing. Based on corpus research, we design rules that make use of multiple morphological categories to improve the lemmatization of noun clusters found in Czech and Croatian corpora. In addition to case, we also take note of gender, animacy, and whether the noun is a proper noun. The improvements lead to more accurate and more unified forms of the terms produced during terminology extraction for these two languages in Sketch Engine.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10200 - Computer and information sciences

Projekt

<a href="/cs/project/LM2023062" target="_blank" >LM2023062: Digitální výzkumná infrastruktura pro jazykové technologie, umění a humanitní vědy</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název statě ve sborníku

Recent Advances in Slavonic Natural Language Processing, RASLAN 2025

ISBN

9788026318583

ISSN

2336-4289

e-ISSN

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Počet stran výsledku

8

Strana od-do

165-172

Název nakladatele

Tribun EU

Místo vydání

Brno, Czech Republic

Místo konání akce

Kouty nad Desnou, Česká Republika

Datum konání akce

1. 1. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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