The Quranic Arabic Corpus (http://corpus.quran.com) is a collaboratively constructed linguistic resource initiated at the University of Leeds, with multiple layers of annotation including part-of-speech tagging, morphological segmentation (Dukes & Habash, 2010) and syntactic analysis using dependency grammar (Dukes & Buckwalter, 2010). The motivation behind this work is to produce a resource that enables further analysis of the Quran, the 1,400 year-old central religious text of Islam. This project contrasts with other Arabic treebanks by providing a deep linguistic model based on the historical traditional grammar known as i'rāb (إعزاة ). By adapting this well-known canon of Quranic grammar into a familiar tagset, it is possible to encoura...
This article describes the process of gathering and constructing a bilingual parallel corpus of Isla...
Modern Standard Arabic is the written standard across the Arab world; but there is an increasing use...
Morphological analyzers and part-of-speech taggers are key technologies for most text analysis appli...
his paper describes the underlying software platform used to develop and publish annotations for the...
Research into statistical parsing for English has enjoyed over a decade of successful results. Howev...
The Quranic Arabic corpus is one of the most important computational tools that has been produced in...
This article discusses the plan to implement the Quranic Arabic Corpus for the development of Arabic...
Natural Language Processing Working Together with Arabic and Islamic Studies is a 2-year project fun...
Recent advances in Text Mining and Natural Language Processing have enabled the development of seman...
Our Artificial Intelligence research group at the University of Leeds has collected, analysed and an...
Some attempts have been made in the academic community to carry out an automatic morphological analy...
This Quran as the central religious text of Islam is widely regarded as the finest work in classical...
Natural Language Processing Working Together with Arabic and Islamic Studies is a 2-year project fun...
This paper presents QurAna: a large corpus created from the original Quranic text, where personal pr...
AQQAC is a collection of approximately 2224 questions and answers about Al-Al-Quran. Each question a...
This article describes the process of gathering and constructing a bilingual parallel corpus of Isla...
Modern Standard Arabic is the written standard across the Arab world; but there is an increasing use...
Morphological analyzers and part-of-speech taggers are key technologies for most text analysis appli...
his paper describes the underlying software platform used to develop and publish annotations for the...
Research into statistical parsing for English has enjoyed over a decade of successful results. Howev...
The Quranic Arabic corpus is one of the most important computational tools that has been produced in...
This article discusses the plan to implement the Quranic Arabic Corpus for the development of Arabic...
Natural Language Processing Working Together with Arabic and Islamic Studies is a 2-year project fun...
Recent advances in Text Mining and Natural Language Processing have enabled the development of seman...
Our Artificial Intelligence research group at the University of Leeds has collected, analysed and an...
Some attempts have been made in the academic community to carry out an automatic morphological analy...
This Quran as the central religious text of Islam is widely regarded as the finest work in classical...
Natural Language Processing Working Together with Arabic and Islamic Studies is a 2-year project fun...
This paper presents QurAna: a large corpus created from the original Quranic text, where personal pr...
AQQAC is a collection of approximately 2224 questions and answers about Al-Al-Quran. Each question a...
This article describes the process of gathering and constructing a bilingual parallel corpus of Isla...
Modern Standard Arabic is the written standard across the Arab world; but there is an increasing use...
Morphological analyzers and part-of-speech taggers are key technologies for most text analysis appli...