ShadowSense: A Multi-annotated Dataset for Evaluating Word Sense Induction
| Authors | |
|---|---|
| Year of publication | 2024 |
| Type | Article in Proceedings |
| Conference | Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024 |
| MU Faculty or unit | |
| Citation | |
| web | https://aclanthology.org/2024.lrec-main.1286/ |
| Keywords | ShadowSense; word sense induction; WSI |
| Description | In this paper we present a novel bilingual (Czech, English) dataset called ShadowSense developed for the purposes of word sense induction (WSI) evaluation. Unlike existing WSI datasets, ShadowSense is annotated by multiple annotators whose inter-annotator agreement represents key reliability score to be used for evaluation of systems automatically inducing word senses. In this paper we clarify the motivation for such an approach, describe the dataset in detail and provide evaluation of three neural WSI systems showing substantial differences compared to traditional evaluation paradigms. © 2024 ELRA Language Resource Association: CC BY-NC 4.0. |
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