SinaTools: Open Source Toolkit for Arabic Natural Language Processing

Tymaa Hammouda, Mustafa Jarrar, Mohammed Khalilia
11/3/2024
cs.CLcs.AI

No confident code implementation found for this paper. 3 possible matches can be shown below.

Abstract

We introduce SinaTools, an open-source Python package for Arabic natural language processing and understanding. SinaTools is a unified package allowing people to integrate it into their system workflow, offering solutions for various tasks such as flat and nested Named Entity Recognition (NER), fully-flagged Word Sense Disambiguation (WSD), Semantic Relatedness, Synonymy Extractions and Evaluation, Lemmatization, Part-of-speech Tagging, Root Tagging, and additional helper utilities such as corpus processing, text stripping methods, and diacritic-aware word matching. This paper presents SinaTools and its benchmarking results, demonstrating that SinaTools outperforms all similar tools on the aforementioned tasks, such as Flat NER (87.33%), Nested NER (89.42%), WSD (82.63%), Semantic Relatedness (0.49 Spearman rank), Lemmatization (90.5%), POS tagging (97.5%), among others. SinaTools can be downloaded from (https://sina.birzeit.edu/sinatools).

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 3 weaker matches are hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{hammouda2024sinatools,
  title  = {SinaTools: Open Source Toolkit for Arabic Natural Language Processing},
  author = {Tymaa Hammouda and Mustafa Jarrar and Mohammed Khalilia},
  year   = {2024},
  eprint = {2411.01523},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2411.01523v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2411.01523.svg)](https://codeofpaper.com/paper/2411.01523)

Discussion