Študija primera za prikaz pristopa k statistični analizi variantnosti večbesednih enot v slovenskih korpusih

In Slovene linguistics, much research in phraseology has either been theoretical in nature or focused more on compiling lexicographic resources for human users. While several machine-readable lexicographic resources containing multiword expressions (MWEs) have also been developed in recent years, Slovene phraseology and computational Slovene linguistics remain largely divided into separate tracks. We attempt to bridge the gap with a brief demonstration of the benefits that computational and statistical approaches based on machine-readable data can have for linguists and phraseologists. We briefly present the SUK Training Corpus of Slovene, the largest machine-readable dataset for Slovene that contains annotations of multiword expressions, as well as the Q-CAT Corpus Annotation Tool that was used to annotate it. We extract examples for two Slovene MWEs (priti na zeleno vejo and podirati se kot hišica iz kart) from the morphosyntactically annotated Gigafida 2.1 Corpus of Written Standard Slovene using a rule-based approach that leverages syntactic structures. We perform a statistical analysis to determine the degree of variation within the extracted examples. We aim to show that machine-readable data is intended not only for developers of NLP tools but can also help provide additional insight into the structure and variation for the linguistic description of MWEs.

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Repository of the University of Ljubljana (University of Ljubljana)
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2026-01-06
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Natural Language Processing Techniques
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Študija primera za prikaz pristopa k statistični analizi variantnosti večbesednih enot v slovenskih korpusih

Jaka Čibej
Repository of the University of Ljubljana (University of Ljubljana)
Natural Language Processing Techniques
article

Študija primera za prikaz pristopa k statistični analizi variantnosti večbesednih enot v slovenskih korpusih

Jaka Čibej
article en

Abstract

In Slovene linguistics, much research in phraseology has either been theoretical in nature or focused more on compiling lexicographic resources for human users. While several machine-readable lexicographic resources containing multiword expressions (MWEs) have also been developed in recent years, Slovene phraseology and computational Slovene linguistics remain largely divided into separate tracks. We attempt to bridge the gap with a brief demonstration of the benefits that computational and statistical approaches based on machine-readable data can have for linguists and phraseologists. We briefly present the SUK Training Corpus of Slovene, the largest machine-readable dataset for Slovene that contains annotations of multiword expressions, as well as the Q-CAT Corpus Annotation Tool that was used to annotate it. We extract examples for two Slovene MWEs (priti na zeleno vejo and podirati se kot hišica iz kart) from the morphosyntactically annotated Gigafida 2.1 Corpus of Written Standard Slovene using a rule-based approach that leverages syntactic structures. We perform a statistical analysis to determine the degree of variation within the extracted examples. We aim to show that machine-readable data is intended not only for developers of NLP tools but can also help provide additional insight into the structure and variation for the linguistic description of MWEs.

Repository of the University of Ljubljana (University of Ljubljana)
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Natural Language Processing Techniques
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Študija primera za prikaz pristopa k statistični analizi variantnosti večbesednih enot v slovenskih korpusih — Jaka Čibej · Repository of the University of Ljubljana (University of Ljubljana) (2026) | TGRS Research Map | TGRS