20.500.12556/RUL-187762 Slovene word-sense disambiguation and novelty detection with dictionary examples Many less-resourced languages struggle with a lack of large, task-specific datasets that are required for solving relevant tasks with modern transformer-based large language models (LLMs). On the other hand, many linguistic resources, such as dictionaries, are rarely used in this context despite their large information contents. We show how LLMs can be used to extend existing language resources in less-resourced languages for two important tasks: word-sense disambiguation (WSD) and threshold-based novelty detection (ND), a task similar to word-sense induction (WSI). We approach the two tasks through the related but much more accessible word-in-context (WiC) task where, given a pair of sentences and a target word, a classification model is tasked with predicting whether the sense of a given word differs between sentences. We demonstrate that a well-trained model for this task can distinguish between different word senses and can be adapted to solve the WSD and ND tasks. The advantage of using the WiC task, instead of directly predicting senses, is that the WiC task does not need pre-constructed sense inventories with a sufficient number of examples for each sense, which are rarely available in less-resourced languages. We show that sentence pairs for the WiC task can be successfully generated from dictionary examples using LLMs. The resulting prediction models outperform existing models on WiC, WSD, and ND tasks. We demonstrate our methodology on the Slovene language, where a monolingual dictionary is available, but word-sense resources are tiny. large language models word-sense disambiguation novelty detection word-in-context dictionary examples veliki jezikovni modeli razdvoumljanje pomenov besed detekcija novih pomenov beseda-v-kontekstu slovarski primeri true false true Angleški jezik Slovenski jezik Članek v reviji 2026-09-14 07:50:47 2026-09-14 07:50:49 2026-09-15 04:27:31 0000-00-00 00:00:00 2026 0 0 15 str. art. 102638 Vol. 166 Nov. 2026 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004.89:81'322 0169-023X 10.1016/j.datak.2026.102638 290903811 RAZ_Skvorc_Tadej_2026.pdf RAZ_Skvorc_Tadej_2026.pdf 1 5368F2D93622A34E6519963EC2B59226 4c01b6a63fc54a43aae0923f93c9d63d45da6fef0b8f00ef15a745ae2cf57a50 b2d1affc-b000-11f1-8bc5-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=247505 https://www.sciencedirect.com/science/article/pii/S0169023X26000856 1 35866dc6-b000-11f1-8bc5-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=247504 Fakulteta za računalništvo in informatiko 0 0 0