Slovene Lexicographic QA Fine-Tuning Corpus SloLexQA 1.0

  Avtorji

Knez, Timotej and Žitnik, Slavko

  Identifikator vnosa

http://hdl.handle.net/11356/2116

 URL projekta

https://www.cjvt.si/llm4dh/

 Datum objave

2026-04-14

 Vrsta

corpus, text

 Velikost

16508 items

 Jezik(i)

Slovenian

 Opis

The Slovene Lexicographic QA Fine-Tuning Corpus is a specialized dataset designed to advance the performance of AI models in understanding the structural, grammatical, and semantic nuances of the Slovene language. Comprising over 16,000 question-answer pairs, the corpus shifts away from general knowledge to focus on high-quality lexicographic data, including morphology, lemmatization, and part-of-speech identification. It serves as a critical resource for fine-tuning models to act as sophisticated linguistic assistants. The dataset integrates diverse sources, ranging from automatically generated content based on the Digital Dictionary Database of Slovene (DDDS) to manual expert advice from the Jezikovna svetovalnica portal. This hybrid approach ensures a robust mix of systematic grammatical queries and nuanced, real-world linguistic explanations. With a significant portion of the data derived from annotated linguistic corpora like SSJ500k, the dataset provides a reliable foundation for training models in both context-free definitions and context-dependent usage scenarios. Technically, the corpus is structured for high utility in machine learning workflows, featuring a 90/10 training and test split with metadata for each entry. It categorizes questions into specific types such as definitions and usage examples, allowing researchers to perform targeted domain adaptation. By providing clear links between questions and specific lexemes, the corpus enables precise evaluation of a model's ability to navigate the formal rules and practical applications of the Slovene lexicon.

 Izdajatelj

Faculty of Computer and Information Science, University of Ljubljana

 Zahvala

ARIS (Slovenian Research and Innovation Agency) GC-0002 "LLM4DH: Large Language Models for Digital Humanities"

European Union HORIZON-WIDERA-2023-TALENTS-01-01 101186647 "EU Era Chair (AI4DH)"

 Ključne besede

question answering Slovene grammar large language models

 Zbirke

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