Enriching the NArabizi Treebank: A Multifaceted Approach to Supporting
  an Under-Resourced Language
Riabi Arij Mahamdi Menel Seddah Djamé
In this paper we address the scarcity of annotated data for NArabizi, a
Romanized form of North African Arabic used mostly on social media, which poses
challenges for Natural Language Processing (NLP). We introduce an enriched
version of NArabizi Treebank (Seddah et al., 2020) with three main
contributions: the addition of two novel annotation layers (named entity
recognition and offensive language detection) and a re-annotation of the
tokenization, morpho-syntactic and syntactic layers that ensure annotation
consistency. Our experimental results, using different tokenization schemes,
showcase the value of our contributions and highlight the impact of working
with non-gold tokenization for NER and dependency parsing. To facilitate future
research, we make these annotations publicly available. Our enhanced NArabizi
Treebank paves the way for creating sophisticated language models and NLP tools
for this under-represented language.