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adawat

The first online catalogue for Arabic NLP tools. This catalogue contains more than 50 tools with around than 25 metadata annotations for each tool. You can view the list of all tools using the link of the webiste https://arbml.github.io/adawat/

Metadata

  • Id tool id
  • Name name of the tool
  • Colab link colab link
  • Link link to the source code or website
  • License license of the tool
  • Released Year year of the publishing the tool/paper
  • GitHub Repo yes or no for GitHub repository
  • Pricing free or paid
  • Accessibility anonymous or requires authentication
  • Description short statement describing the tool
  • Version version of the tool
  • Paper Title title of the published paper
  • Paper URL url of the published paper
  • Tasks the tasks included in the tool spearated by comma
  • Interface cli of gui
  • Programming Language i.e python, java, etc.
  • Evaluated datasets datasets used for evaluating, contains ids of masader datasets
  • Added by name of the contributer

Access Data

You can access the annoated tool using datasets

from datasets import load_dataset
adawat = load_dataset('arbml/adawat')
adawat['train'][0]

which gives the following output

{'Id': '1',
 'Name': 'pyarabic',
 'Link': 'https://github.com/linuxscout/pyarabic',
 'Colab link': 'https://colab.research.google.com/github/ARBML/adawat/blob/main/notebooks/pyarabic.ipynb',
 'GitHub Repo': 'Yes',
 'Pricing': 'Free',
 'Accessibility': 'Anonymous',
 'License': 'unknown',
 'Version': '0.6.14',
 'Description': 'A specific Arabic language library for Python, provides basic functions to manipulate Arabic letters and text, like detecting Arabic letters, Arabic letters groups and characteristics, remove diacritics etc.',
 'Paper Title': 'nan',
 'Paper URL': 'nan',
 'Release Year': 2010,
 'Tasks': 'Preprocessing',
 'Supported language(s)': 'Classic Arabic, Arabic MSA, Dialectal Arabic',
 'Tool Type': 'Package',
 'Interface': 'Command Line Interface (CLI)',
 'Programming Language': 'Python',
 'Added by': 'Zaid Alyafeai',
 'Evaluated datasets': 'nan'}

Running Masader locally with Jekyll

Prerequisites:

  1. Install Ruby.
  2. Install bundle.
  3. Install Jekyll.

Steps:

  1. Open the project in the terminal
  2. Run bundle install to install dependencies.
  3. Run the site locally with bundle exec jekyll serve.
  4. Preview Masader site on your web browser by navigate to http://127.0.0.1:4000/masader/.

Note: Navigate to the publishing source for MASADER site. For more information about publishing sources, see.

Contribution

The catalogue will be updated regularly. If you want to add a new tool, use this form.

To contribute to the project development, please visit contributing instructions

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