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2022 EMNLP EMNLP 2022

ArabIE: Joint Entity, Relation and Event Extraction for Arabic

Abstract

AbstractPrevious work on Arabic information extraction has mainly focused on named entity recognition and very little work has been done on Arabic relation extraction and event recognition. Moreover, modeling Arabic data for such tasks is not straightforward because of the morphological richness and idiosyncrasies of the Arabic language. We propose in this article the first neural joint information extraction system for the Arabic language.

🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio

Authors

Niama El Khbir , Nadi Tomeh , Thierry Charnois

Topics

Natural Language Processing > Applications > Information Extraction Natural Language Processing > Resources & Methods > Multilingual NLP

Keywords

relation extraction named entity recognition joint extraction event extraction arabic language
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