Below are some useful Arabic corpora for researchers working on Arabic Natural Language Processing and Computational Linguistics.
1- KALIMAT a Multipurpose Arabic Corpus
Multipurpose Arabic Corpus
We are pleased to announce the immediate availability of KALIMAT 1.0,
KALIMAT is an Arabic natural language resource that consists of:
1) 20,291 Arabic articles collected from the Omani newspaper Alwatan by (Abbas et al. 2011).
2) 20,291 Extractive Single-document system summaries.
3) 2,057 Extractive Multi-document system summaries.
4) 20,291 Named Entity Recognised articles.
5) 20,291 Part of Speech Tagged articles.
6) 20,291 Morphologically Analyse articles.
The data collection articles fall into six categories:
culture, economy, local-news, international-news, religion, and sports.
Click here to download the corpus
2- Essex Arabic Summaries Corpus (EASC)
Click the link
below for a copy of EASC Corpus:
Download 2013 Corpus
The EASC is an Arabic natural language resources. It contains 153 Arabic articles and 765 human-generated extractive summaries of those articles. These summaries were generated using Mechanical Turk (http://www.mturk.com/).
Among the major features of EASC are:
Names and extensions are formatted to be compatible with current evaluation systems such as ROUGE and AutoSummENG. Available in two encoding formats UTF-8 and ISO-8859-6 (Arabic).
The Essex Arabic Summaries Corpus (EASC) uses copyright material. Users of the corpus are responsible for ensuring that they comply with the terms of the copyrights that apply to the source material and the derived works (summaries) and the terms of relevant copyright law.
Any other original data that is distributed with this corpus is made available under the Creative Commons Attributive/Share Alike license (http://creativecommons.org/licenses/by-sa/3.0/). You must provide details of the source of the material when using it.
3- Multi-document Summaries Corpora
The dataset is derived from publicly available WikiNews (http://www.wikinews.org/) English texts.
The source texts
were under CC Attribution Licence V2.5 (cf. http://creativecommons.org/licenses/by/2.5/).
Texts in other languages have been translated by native speakers of each
The dataset can be downloaded from here
The documents hold no meta-data or tags: they consist plain text files encoded in UTF-8 (without a Byte Order Marker - BOM).
Tables and formatting have been removed.
700 files are contained in the dataset, 100 for each of the following languages:
Visit the following for the corpora license agreement and description: