Work

ANETAC: Arabic Named Entity Transliteration and Classification Dataset

Year: 2019

Type: preprint

Abstract: 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.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.1907.03110

Authors: Ameur, Mohamed Seghir Hadj, Meziane, Farid, Guessoum, Ahmed

Institutions: University of Salford, University of Sciences and Technology Houari Boumediene

Language: English

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2954982483

Cites: 8

Cited by: 2

Related to: 20