MAKED: Multi-lingual Automatic Keyword Extraction Dataset
Yash Verma, Anubhav Jangra, Sriparna Saha, Adam Jatowt, Dwaipayan Roy
Abstract
Keyword extraction is an integral task for many downstream problems like clustering, recommendation, search and classification. Development and evaluation of keyword extraction techniques require an exhaustive dataset; however, currently, the community lacks large-scale multi-lingual datasets. In this paper, we present MAKED, a large-scale multi-lingual keyword extraction dataset comprising of 540K+ news articles from British Broadcasting Corporation News (BBC News) spanning 20 languages. It is the first keyword extraction dataset for 11 of these 20 languages. The quality of the dataset is examined by experimentation with several baselines. We believe that the proposed dataset will help advance the field of automatic keyword extraction given its size, diversity in terms of languages used, topics covered and time periods as well as its focus on under-studied languages.- Anthology ID:
- 2022.lrec-1.664
- Volume:
- Proceedings of the Thirteenth Language Resources and Evaluation Conference
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 6170–6179
- Language:
- URL:
- https://aclanthology.org/2022.lrec-1.664
- DOI:
- Cite (ACL):
- Yash Verma, Anubhav Jangra, Sriparna Saha, Adam Jatowt, and Dwaipayan Roy. 2022. MAKED: Multi-lingual Automatic Keyword Extraction Dataset. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 6170–6179, Marseille, France. European Language Resources Association.
- Cite (Informal):
- MAKED: Multi-lingual Automatic Keyword Extraction Dataset (Verma et al., LREC 2022)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/2022.lrec-1.664.pdf
- Data
- XL-Sum