ANETAC: Arabic Named Entity Transliteration and Classification Dataset
This provides a new dataset for researchers working on Arabic named entity transliteration and classification, but it is incremental as it builds on existing parallel translation corpora.
The authors introduced ANETAC, a freely accessible English-Arabic named entity transliteration and classification dataset with 79,924 instances, each containing an English named entity, its Arabic transliteration, and a class (Person, Location, or Organization). This dataset addresses the need for resources in Arabic named entity processing, enabling research in transliteration and classification tasks.
In this paper, we make freely accessible ANETAC our English-Arabic named entity transliteration and classification dataset that we built from freely available parallel translation corpora. The dataset contains 79,924 instances, each instance is a triplet (e, a, c), where e is the English named entity, a is its Arabic transliteration and c is its class that can be either a Person, a Location, or an Organization. The ANETAC dataset is mainly aimed for the researchers that are working on Arabic named entity transliteration, but it can also be used for named entity classification purposes.