Exploring the Effects of Stemming on Arabic Named Entity Recognition
Ismail El Bazi, Nabil Laachfoubi · International Journal of Artificial Intelligence & Applications · 2016
Stemming is the process of reducing words to their stems or roots.Due to the morphological richness and complexity of the Arabic language, stemming is an essential part of most Natural Language Processing (NLP) tasks for this language.In this paper, we study the impact of different stemming approaches on the Named Entity Recognition (NER) task for Arabic and explore the merits, limitations and differences between light stemming and root-extraction methods.Our experiments are evaluated on the standard ANERCorp dataset as well as the AQMAR Arabic Wikipedia Named Entity Corpus.