AgaCKNER: First Kurdish Sorani Named Entity Recognition Dataset

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 OUTSIDE. 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.

AgaCKNER是首个公开可获取的库尔德语索拉尼方言命名实体识别（Named Entity Recognition, NER）数据集，旨在推动低资源语言处理领域的研究。该数据集源自鲁道媒体网络（Rudaw Media Network），涵盖库尔德新闻、中东新闻、世界新闻、经济新闻及体育新闻五大领域的多元主题，所有内容均从160余篇文章中精心遴选而成。数据集包含2534个句子与64563个Token，已针对NER任务完成预处理，并采用CoNLL格式编排。实体以BIO格式标注，共分为五类：PERSON（人物）、LOCATION（地点）、ORGANIZATION（组织）、DATE（日期）及OUTSIDE（非实体）。AgaCKNER是库尔德语索拉尼方言自然语言处理研究的核心资源，极大推动了低资源语言领域的学术探索。其结构化设计便于快速生成训练集、验证集与测试集的划分。

搜集汇总

背景与挑战

背景概述

AgaCKNER是首个公开可用的库尔德索拉尼语命名实体识别数据集，旨在推动低资源语言处理研究。它基于Rudaw Media Network的160多篇文章构建，涵盖新闻、经济、体育等多个领域，包含2,534个句子和64,563个标记，采用CoNLL格式和BIO标注，实体类别包括人物、地点、组织、日期等。该数据集结构清晰，便于分割用于模型训练和评估。