StoryDB: Broad Multi-language Narrative Dataset

Alexey Tikhonov, Igor Samenko, Ivan Yamshchikov


Abstract
This paper presents StoryDB — a broad multi-language dataset of narratives. StoryDB is a corpus of texts that includes stories in 42 different languages. Every language includes 500+ stories. Some of the languages include more than 20 000 stories. Every story is indexed across languages and labeled with tags such as a genre or a topic. The corpus shows rich topical and language variation and can serve as a resource for the study of the role of narrative in natural language processing across various languages including low resource ones. We also demonstrate how the dataset could be used to benchmark three modern multilanguage models, namely, mDistillBERT, mBERT, and XLM-RoBERTa.
Anthology ID:
2021.eval4nlp-1.4
Volume:
Proceedings of the 2nd Workshop on Evaluation and Comparison of NLP Systems
Month:
November
Year:
2021
Address:
Punta Cana, Dominican Republic
Editors:
Yang Gao, Steffen Eger, Wei Zhao, Piyawat Lertvittayakumjorn, Marina Fomicheva
Venue:
Eval4NLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
32–39
Language:
URL:
https://aclanthology.org/2021.eval4nlp-1.4
DOI:
10.18653/v1/2021.eval4nlp-1.4
Bibkey:
Cite (ACL):
Alexey Tikhonov, Igor Samenko, and Ivan Yamshchikov. 2021. StoryDB: Broad Multi-language Narrative Dataset. In Proceedings of the 2nd Workshop on Evaluation and Comparison of NLP Systems, pages 32–39, Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
StoryDB: Broad Multi-language Narrative Dataset (Tikhonov et al., Eval4NLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.eval4nlp-1.4.pdf
Data
StoryDB