Cross-lingual Named Entity Corpus for Slavic Languages

This paper presents a corpus manually annotated with named entities for six Slavic languages — Bulgarian, Czech, Polish, Slovenian, Russian, and Ukrainian. This work is the result of a series of shared tasks, conducted in 2017–2023 as a part of the Workshops on Slavic Natural Language Processing. The corpus consists of 5,017 documents on seven topics. The documents are annotated with five classes of named entities. Each entity is described by a category, a lemma, and a unique cross-lingual identifier. We provide two train-tune dataset splits — single topic out and cross topics. For each split, we set benchmarks using a transformer-based neural network architecture with the pre-trained multilingual models — XLM-RoBERTa-large for named entity mention recognition and categorization, and mT5-large for named entity lemmatization and linking.