The expanding financial markets of the Arab world require sophisticated Arabic NLP tools.
To address this need within the banking domain, the Arabic Financial NLP (AraFinNLP) …

We present WojoodNER-2024, the second Arabic Named Entity Recognition (NER) Shared
Task. In WojoodNER-2024, we focus on fine-grained Arabic NER. We provided participants …

SALMA, the first Arabic sense-annotated corpus, consists of~ 34K tokens, which are all
sense-annotated. The corpus is annotated using two different sense inventories …

Traditional NER systems are typically trained to recognize coarse-grained entities, and less
attention is given to classifying entities into a hierarchy of fine-grained lower-level subtypes …

This paper presents an overview of the Arabic Natural Language Understanding
(ArabicNLU 2024) shared task, focusing on two subtasks: Word Sense Disambiguation …

The proliferation of bias and propaganda on social media is an increasingly significant
concern, leading to the development of techniques for automatic detection. This article …

Event-argument extraction is a challenging task, particularly in Arabic due to sparse
linguistic resources. To fill this gap, we introduce the\hadath corpus ($550 $ k tokens) as an …

Abstract The Wojood Named Entity Recognition (NER) shared task introduces a
comprehensive Arabic NER dataset encompassing both flat and nested entity tasks …

Abstract Named Entity Recognition (NER) is a crucial task in natural language processing
that facilitates the extraction of vital information from text. However, NER for Arabic presents …

Named entity recognition (NER) is one of many challenging tasks in Arabic Natural
Language Processing. It is also the base of many critical downstream tasks to help …