Work

LIPN at WojoodNER shared task: A Span-Based Approach for Flat and Nested Arabic Named Entity Recognition

Year: 2023

Type: conference-paper

Abstract: The Wojood Named Entity Recognition (NER) shared task introduces a comprehensive Arabic NER dataset encompassing both flat and nested entity tasks, addressing the challenge of limited Arabic resources.In this paper, we present our team LIPN approach to addressing the two subtasks of WojoodNER Shared-Task.We frame NER as a span classification problem.We employ a pretrained language model for token representations and neural network classifiers.We use global decoding for flat NER and a greedy strategy for nested NER.Our model secured the first position in flat NER and the fourth position in nested NER during the competition, with an F-score of 91.96 and 92.45 respectively.Our code is publicly available (https://github.com/niamaelkhbir/ LIPN-at-WojoodSharedTask).

Source: Arabic Natural Language Processing Conference (ArabicNLP)

DOI: 10.18653/v1/2023.arabicnlp-1.89

Authors: Niama Elkhbir, Urchade Zaratiana, Nadi Tomeh, Thierry Charnois

Institutions: Centre National de la Recherche Scientifique, Laboratoire d'Informatique de Paris-Nord, FI Group (Portugal)

Language: English

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: Agence Nationale de la Recherche, Grand Équipement National De Calcul Intensif

Awards: Empirical Foundations of Linguistics : data, methods, models, G7240651115