Towards relation extraction from Arabic text: a review

Abstract

Semantic relation extraction is an important component of ontologies that can support many applications e.g. text mining, question answering, and information extraction. However, extracting semantic relations between concepts is not trivial and one of the main challenges in Natural Language Processing (NLP) Field. The Arabic language has complex morphological, grammatical, and semantic aspects since it is a highly inflectional and derivational language, which makes task even more challenging. In this paper, we present a review of the state of the art for relation extraction from texts, addressing the progress and difficulties in this field. We discuss several aspects related to this task, considering the taxonomic and non-taxonomic relation extraction methods. Majority of relation extraction approaches implement a combination of statistical and linguistic techniques to extract semantic relations from text. We also give special attention to the state of the work on relation extraction from Arabic texts, which need further progress.

FarsBase-KBP: A Knowledge Base Population System for the Persian Knowledge Graph

“…AlArfaj have reviewed the different state-of-the-art RE methods for Arabic and showed that the majority of RE approaches utilize a combination of statistical and linguistic-pattern techniques. The review proposes that linguistic-pattern methods provide high precision, but their recall is very low, and patterns are specified in the regular expression form, which is challenging to cope with language variety [43].…”