RuCoCo: a new Russian corpus with coreference annotation
Vladimir Dobrovolskii, Mariia Michurina, Alexandra Ivoylova
TL;DR
RuCoCo is a large Russian corpus with coreference annotations, combining machine-generated and human-refined annotations to facilitate research in Russian NLP.
Contribution
This paper introduces RuCoCo, a new large-scale Russian coreference corpus with high inter-annotator agreement, combining manual and machine annotations.
Findings
Corpus contains 1 million words and 150,000 mentions.
High inter-annotator agreement achieved.
Publicly available resource for NLP research.
Abstract
We present a new corpus with coreference annotation, Russian Coreference Corpus (RuCoCo). The goal of RuCoCo is to obtain a large number of annotated texts while maintaining high inter-annotator agreement. RuCoCo contains news texts in Russian, part of which were annotated from scratch, and for the rest the machine-generated annotations were refined by human annotators. The size of our corpus is one million words and around 150,000 mentions. We make the corpus publicly available.
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Taxonomy
TopicsNatural Language Processing Techniques · Topic Modeling · Speech and dialogue systems