mlsanityData to 14 Oct 2026

RuDSI: graph-based word sense induction dataset for Russian

arXiv 2209.13750 ↗First posted 28 Sep 2022cs.CLcited by 7

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Abstract (arXiv)

We present RuDSI, a new benchmark for word sense induction (WSI) in Russian. The dataset was created using manual annotation and semi-automatic clustering of Word Usage Graphs (WUGs). Unlike prior WSI datasets for Russian, RuDSI is completely data-driven (based on texts from Russian National Corpus), with no external word senses imposed on annotators. Depending on the parameters of graph clustering, different derivative datasets can be produced from raw annotation. We report the performance that several baseline WSI methods obtain on RuDSI and discuss possibilities for improving these scores.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 8 of its 31 references that are in the map. First posted on arXiv 28 Sep 2022.

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8 of 31 references.

References · 8

  1. 2020SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detectioncited by 108
  2. 2021DWUG: A large Resource of Diachronic Word Usage Graphs in Four Languagescited by 26
  3. 2019Towards better substitution-based word sense inductioncited by 18
  4. 2020RuSemShift: a dataset of historical lexical semantic change in Russiancited by 16
  5. 2021Three-part diachronic semantic change dataset for Russiancited by 11
  6. 2018RUSSE'2018: A Shared Task on Word Sense Induction for the Russian Languagecited by 4
  7. 2020Word Sense Disambiguation for 158 Languages using Word Embeddings Onlycited by 4
  8. 2021Unreasonable Effectiveness of Rule-Based Heuristics in Solving Russian SuperGLUE Taskscited by 1

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Citing papers per year: 2023: 1; 2024: 4; 2025: 2.

7 papers.