HaRuCo: a New Russian-Language Corpus of Popular Science Texts with Coreference Annotation
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Abstract
This paper presents a new Russian-language corpus with coreference annotation, HaRuCo (Habr Russian Coreference Corpus). The corpus is based on popular science articles related to the subject area of “Computational Linguistics.” The paper proposes a method for coreference annotation in texts from narrow subject areas, which includes four main stages: syntactic analysis of the text, assembly of noun phrases and identification of pronouns for constructing mentions (spans), classification of mentions by subject area classes, and clustering of mentions according to chains of coreferentially linked spans. Coreferential links were annotated using a syntactic parser and a large language model, followed by manual verification and correction. The created corpus includes 3.727 entities, 9.905 mentions, and 2.683 coreferential chains. The created corpus can be used for training and evaluating coreference resolution models for the Russian language.
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References
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