AgaCKNER: First Kurdish Sorani Named Entity Recognition Dataset
Description
AgaCKNER is the first publicly accessible Named Entity Recognition (NER) dataset in the Kurdish Sorani language, developed to advance research in low-resource language processing. Derived from the Rudaw Media Network, AgaCKNER encompasses a broad array of topics across five distinct domains: Kurdistan news, Middle East news, world news, economic news, and sports news that are meticulously curated from over 160 articles. The dataset includes 2,534 sentences and 64,563 tokens, pre-processed and formatted in CoNLL for NER tasks. Entities are labelled in BIO format under five categories: PERSON, LOCATION, ORGANIZATION, DATE, and Miscellaneous. AgaCKNER is an essential resource for Kurdish Sorani natural language processing, greatly enhancing research in low-resource languages. Its structure makes it easily adaptable for generating training, validation, and test splits.
Files
Steps to reproduce
The textual data used in the creation of this Named Entity Recognition (NER) dataset were sourced from the Rudaw network. Comprehensive details concerning the data collection and processing methodologies are provided in the article entitled "AgaCKNER: the first Kurdish Sorani Named Entity Recognition dataset."
Institutions
- Sulaimani Polytechnic University
- Swansea University