Lost in Morphology - Enhancing Bilingual Lexicon Induction with Lemmatisation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F25%3A00142848" target="_blank" >RIV/00216224:14330/25:00142848 - isvavai.cz</a>

Výsledek na webu

<a href="https://raslan2025.nlp-consulting.net/" target="_blank" >https://raslan2025.nlp-consulting.net/</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Lost in Morphology - Enhancing Bilingual Lexicon Induction with Lemmatisation

Popis výsledku v původním jazyce

Bilingual Lexicon Induction (BLI) is a fundamental task in cross-lingual word embedding (CWE) evaluation, aimed at retrieving word translations from monolingual corpora in two languages. However, morphological complexity poses an intractable challenge, where translations deemed incorrect tend to be morphological variations of the correct ones. This study explores the role of lemmatisation in mitigating this issue by comparing two integration strategies: (1) pre-alignment lemmatisation, applied before training monolingual word embeddings (MWEs), and (2) post-retrieval lemmatisation, applied to retrieved target words. We conduct experiments using three state-of-the-art CWEs across a wide range of language pairs, comparing Slavonic and other language families, with varying morphological complexity. Our findings reveal notable differences between the two approaches: post-retrieval lemmatisation proves more beneficial for less morphologically complex language pairs, while pre-alignment lemmatisation performs well for those with moderate complexity, and for highly inflected languages, the choice of approach has minimal impact.

Název v anglickém jazyce

Lost in Morphology - Enhancing Bilingual Lexicon Induction with Lemmatisation

Popis výsledku anglicky

Bilingual Lexicon Induction (BLI) is a fundamental task in cross-lingual word embedding (CWE) evaluation, aimed at retrieving word translations from monolingual corpora in two languages. However, morphological complexity poses an intractable challenge, where translations deemed incorrect tend to be morphological variations of the correct ones. This study explores the role of lemmatisation in mitigating this issue by comparing two integration strategies: (1) pre-alignment lemmatisation, applied before training monolingual word embeddings (MWEs), and (2) post-retrieval lemmatisation, applied to retrieved target words. We conduct experiments using three state-of-the-art CWEs across a wide range of language pairs, comparing Slavonic and other language families, with varying morphological complexity. Our findings reveal notable differences between the two approaches: post-retrieval lemmatisation proves more beneficial for less morphologically complex language pairs, while pre-alignment lemmatisation performs well for those with moderate complexity, and for highly inflected languages, the choice of approach has minimal impact.

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

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the Nineteenth Workshop on Recent Advances in Slavonic Natural Languages Processing

ISBN

9788026318583

ISSN

2336-4289

e-ISSN

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Počet stran výsledku

12

Strana od-do

3-14

Název nakladatele

Tribun EU

Místo vydání

Brno

Místo konání akce

Kouty nad Desnou, Česká Republika

Datum konání akce

1. 1. 2025

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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