RUSSE'2020: Findings of the First Taxonomy Enrichment Task for the Russian language
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Abstract (arXiv)
This paper describes the results of the first shared task on taxonomy enrichment for the Russian language. The participants were asked to extend an existing taxonomy with previously unseen words: for each new word their systems should provide a ranked list of possible (candidate) hypernyms. In comparison to the previous tasks for other languages, our competition has a more realistic task setting: new words were provided without definitions. Instead, we provided a textual corpus where these new terms occurred. For this evaluation campaign, we developed a new evaluation dataset based on unpublished RuWordNet data. The shared task features two tracks: "nouns" and "verbs". 16 teams participated in the task demonstrating high results with more than half of them outperforming the provided baseline.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 22 May 2020.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 2.
3 papers.
- 2024Exploring Prompt-Based Methods for Zero-Shot Hypernym Prediction with Large Language Modelscited by 1
- 2024Using Zero-shot Prompting in the Automatic Creation and Expansion of Topic Taxonomies for Tagging Retail Banking Transactionscited by 1
- 2022Taxonomy Enrichment with Text and Graph Vector Representationscited by 0
- 2024Exploring Prompt-Based Methods for Zero-Shot Hypernym Prediction with Large Language Models9 Jan 2024
- 2024Using Zero-shot Prompting in the Automatic Creation and Expansion of Topic Taxonomies for Tagging Retail Banking Transactions8 Jan 2024
- 2022Taxonomy Enrichment with Text and Graph Vector Representations21 Jan 2022