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Corpus resources for learning Arabic to understand the Quran Higher Education Academy workshop on "The Role of Corpora in LSP (Language for Specific Purposes)

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Presentation on theme: "Corpus resources for learning Arabic to understand the Quran Higher Education Academy workshop on "The Role of Corpora in LSP (Language for Specific Purposes)"— Presentation transcript:

1 Corpus resources for learning Arabic to understand the Quran Higher Education Academy workshop on "The Role of Corpora in LSP (Language for Specific Purposes) Learning and Teaching" Parkinson B08, University of Leeds, Monday 23rd July Eric Atwell I-AIBS Institute for Artificial Intelligence and Biological Systems School of Computing University of Leeds

2 (1) Quranic Studies (3) Computing (2) Traditional Arabic Linguistics An Artificial Intelligence interdisciplinary approach to understanding the Quran

3 (1) What is the Quran? Holy BookProphetText Dated Suhuf Ibrahim (Scrolls)Abraham? Tawrat (Torah)Moses1500 BCE? Zabur (Psalms)David1000 BCE? Injil (Gospel)Jesus1 CE The QuranMuhammad (PBUH) CE Islam: the last in a series of 5 religious texts

4 (1) What is the Quran? -Classical Arabic, years ago - All believers should learn the text; translations are interpretations - Islamic Law (legal logic) - Divine guidance & direction - Science and philosophy - Has inspired Algebra, Linguistics The central religious text of Islam

5 (2) Traditional Arabic Linguistics - Orthography (diacritics and vowelization) - Etymology (Semitic roots) - Morphology (derivation and inflection) - Syntax (origins of dependency grammar) - Discourse Analysis & Rhetoric - Semantics & Pragmatics Originated in Arabs studying the language of the Quran (scientific analysis for at least 1000 years – a lot older than English language!):

6 (3) Computing Quran is online, for keyword search BUT verse-by-verse translations are interpretations Muslims should access the true Classical Arabic source

7 (3) Computing Example question-answering dialog system: Question How long should I breastfeed my child for? Answer Mothers should suckle their offspring for two years, if the father wishes to complete the term (The Holy Quran, Verse 2:233). - How far can we go? - An Artificial Intelligence system which understands the Quran?

8 An Artificial Intelligence approach to understanding the Quran Central Hypothesis Augmenting the text of the Quran with rich linguistic annotation will lead to a more intelligent/accurate AI systems. - Prepare the data by annotating the Quran. - Use the data to build an AI system for concept search and question-answering.

9 Corpus resources for learning Arabic to understand the Quran Augmenting the Arabic text of the Quran with rich linguistic annotation will help learners to understand Quranic Arabic. - Annotate the Quranic Arabic Corpus. - Teacher and Learners use the annotations for deeper understanding of Quranic Arabic.

10 Straw Poll: LSP for religious texts? How many Muslims in the audience? – How many read/recite Classical Arabic Quran? – How many would like to? How many Jews in the audience? – How many read/recite Classical Hebrew Tanakh? – How many would like to? How many Christians in the audience? – How many read/recite Classical Hebrew/Greek Bible? – How many would like to? Have I left anyone out?

11 Annotating the Quran Challenges Orthography - Complex non-standard script Morphology (word structure) - Arabic is highly inflected, challenging to analyze Grammar - Phrase structure, dependency Semantics – Ontology of Entities and Concepts referred to by pronouns and nouns

12 Annotating the Quran Solutions - Computing advances have made annotation possible, to high accuracy - Leverage existing resources from Traditional Arabic Grammar -Machine-Learning annotation followed by manual verification -- Community effort using online volunteers

13 Recent Advances: Orthography Google Search for verse (68:38) on Jan 21, 2008 shows many typos An accurate digital copy of the Quran? Encoding Issues - Missing diacritics - Simplified script (not Uthmani) - Windows code page 1256, not Unicode

14 Recent Advances: Orthography Tanzil Project (http://tanzil.info)http://tanzil.info - Stable version released May Uses Unicode XML encoding, including the special characters designed for the complex Arabic script of the Quran - Manually verified to 100% accuracy by a group of experts who have memorized the entire text of the Quran

15 Recent Advances: Orthography Java Quran API (http://jqurantree.org)http://jqurantree.org (Dukes 2009) - Java classes for querying the Tanzil XML of the Quran - gives authentic script on web-pages

16 Recent Advances: Morphology - Buckwalter Arabic Morphological Analyzer (Tim Buckwalter, 2002) - Morphological Analysis of the Quran at the University of Haifa (Shuly Wintner, 2004) - Lexeme & feature based morphological representation of Arabic (Nizar Habash, 2006)

17 The Haifa Corpus (2004) Multiple analysis for each word (up to 5) rbb+fa&l+Noun+Triptotic+Masc+Sg+Pron+Dependent+1P+Sg rbb+fa&l+Noun+Triptotic+Masc+Sg+Gen Not manually verified Authors reports an F-measure of 86% Non-standard annotation scheme not familiar to Arabic linguists e.g. extracting a list of all verbs is non-trivial Arabic text is only encoded phonetically not familiar to Arabic linguists e.g. searching for a specific root is not easy

18 The Quranic Arabic Corpus Kais DukesKais Dukes – PhD (part-time) word structure - colour-coded morphological analysis translation – verse, word-for-word English translations grammar- dependency parse following Arabic tradition semantics – ontology of entities and concepts Machine Learning - annotations used for A.I. training Impact - dozens of researchers have collaborated/cited, and over a million visitors use the website per year

19 The Quranic Arabic Corpus Verified Uthmani Script - Unicode Uthmani Script - Sourced from the verified Tanzil project

20 The Quranic Arabic Corpus Phonetics (faja'alnāhumu) - Phonetic transcription generated algorithmically - Guided by Arabic vowelized diacritics

21 The Quranic Arabic Corpus Interlinear translation - Word-for-word translation from accepted sources - Interlinear translation scheme

22 The Quranic Arabic Corpus Location Reference (21:70:4) - Common standard for verses (Chapter:Verse) - Extended in the QAC corpus to include word numbers and segment numbers, e.g. (21:70:4:2)

23 The Quranic Arabic Corpus Morphological Segmentation - Division of a single word into multiple segments - Part-of-speech tag assigned to each segment - Traditional Arabic Grammar rules used for division

24 The Quranic Arabic Corpus Morphological segment features

25 The Quranic Arabic Corpus Arabic Grammar Summary

26 The Quranic Arabic Corpus Syntactic Annotation - Dependency Grammar based onإعراب (i'rāb) - Syntactico-semantic roles for each word

27 The Quranic Arabic Corpus Ontology of entities and concepts - linked to/from nouns and pronouns in the text

28 The Quranic Arabic Corpus Framework for collaboration User Interaction via Message Board: If you come across a word and you feel that a better analysis could be provided, you can suggest a correction online by clicking on an Arabic word (5000+ resolved messages) Resources: Publications; Citations, Reviews, FAQs, Feedback, Data Download, Software download, Mailing list

29 The Quranic Arabic Corpus Users: researchers, public - Artificial Intelligence and Computational Linguistics - Arabic linguistics -Quranic and Islamic Studies -Classical literature analysis -Anyone who wants to appreciate the Quran

30 The Quranic Arabic Corpus new Computational Linguistics - First Treebank of Classical Arabic - Free Treebank of the Quran - First formal representation of Traditional Arabic Grammar using constituency/dependency graphs - Machine-Learning parser

31 User Feedback (300+ comments) I would like to applaud you for your effort Prof Behnam Sadeghi, Stanford University We are big admirers of the work Prof Gregory Crane, Classics Dept, Tufts University I regularly use your work on the Qur'an and read it whenever I can. Prof Yousuf Islam, Director, Daffodil International University Congratulations to all concerned on this project - Prof Michael Arthur, VC, Leeds Uni

32 Most users are teachers and learners of Quranic Arabic Over a million users already, and growing; many unforseen social benefits, eg: I work as a chaplain in correctional centers in the State of Missouri, U.S.A. Thanks for your permission to use the Quranic Arabic Corpus in these correctional centers Tadar Wazir.

33 AI for understanding the Quran QuranyQurany the first Quran "search for a concept" website If you choose from the tree of concepts on the left hand side concept "Pillars of Islam" then "The Prayers" then "Performing the Prayers" then "Friday Prayers...you get Quran verses on this topic in the upper right frame and Hadith on this topic in the lower right frame. Nora Abbas, Qurany: A Tool to Search for Concepts in the Quran (PDF) Qurany: A Tool to Search for Concepts in the QuranPDF

34 Google Qurany" html version at Store each Quran or Haddith verse as a separate web-page, and annotate each web-page with English translations and concept-tags. Then search is enabled via Google, but "keywords can be concept-tags and/or English words and/or Arabic words. Google "Jesus site:http://www.comp.leeds.ac.uk/nora/htmlJesus site:http://www.comp.leeds.ac.uk/nora/html Google Friday Prayers site:http://www.comp.leeds.ac.uk/nora/htmlFriday Prayers site:http://www.comp.leeds.ac.uk/nora/html

35 AI for understanding the Quran - Tools and resources for text mining the Quran including pronoun references, related verses, lemma concordance and collocation, and text mining the Hadeethtext mining the Quranpronoun referencesrelated verses lemma concordancecollocationtext mining the Hadeeth Abdul-Baquee Sharaf and Eric Atwell (2012). QurAna: Corpus of the Quran annotated with Pronominal Anaphora. Proc LREC2012, Istanbul Abdul-Baquee Sharaf and Eric Atwell (2012). QurSim: A corpus for evaluation of relatedness in short texts. Proc LREC2012, Istanbul

36 QurSimQurSim - 7,679 pairs of related verses, according to Ibn Kathir, respected Islamic Scholar QurAnaQurAna - 24,668 pronouns, each linked to its anaphoric referent entity or concept, and the location of the antecedent if available. Concept listConcept list - a list of 1054 entities or concepts arising from Pronoun referents in the Quran – nominal entities in a Quran ontology

37 AI for understanding the Quran SALMA – Sawalha Atwell Leeds Morphological Analyser SALMA Morphological analysis of Quran text Majdi Sawalha, Eric Atwell (2010). Fine-Grain Morphological Analyzer and Part-of-Speech Tagger for Arabic Text. Proc LREC2010, Valetta, Malta Majdi Sawalha, Eric Atwell (2010). Constructing and Using Broad-Coverage Lexical Resource for Enhancing Morphological Analysis of Arabic. Proc LREC2010, Valetta, Malta

38 AI for understanding the Quran Boundary-Annotated Quran - Tagged with prosodic annotation scheme from Tajwīd (recitation) mark-up in the Qur'an Claire BrierleyClaire Brierley, Majdi Sawalha and Eric Atwell (2012). Open-Source Boundary-Annotated Corpus for Arabic Speech and Language Processing. Proc LREC2012, IstanbulMajdi SawalhaEric Atwell Majdi SawalhaMajdi Sawalha, Claire Brierley and Eric Atwell (2012). Predicting Phrase Breaks in Classical and Modern Standard Arabic Text. Proc LREC2012, IstanbulClaire BrierleyEric Atwell

39 AI for understanding the Quran The Quranic Arabic Corpus - the first online annotated linguistic resource which shows the Arabic "irab" morphology and grammar for each word and verse in the Holy Quran, including word-by-word morphology and English gloss, and Ontology of Quranic conceptsQuranic Arabic Corpusword-by-word morphology and English glossOntology of Quranic concepts Kais Dukes, Eric Atwell and Nizar Habash (2011). Supervised Collaboration for Syntactic Annotation of Quranic Arabic. Language Resources and Evaluation Journal (LREJ). Kais DukesKais Dukes and Eric Atwell (2012). LAMP: A Multimodal Web Platform for Collaborative Linguistic Analysis. Proc LREC2012, IstanbulEric Atwell

40 Conclusion Augmenting the Arabic text of the Quran with rich linguistic annotation will help learners to understand Quranic Arabic. Eric Atwell, Nora Abbas, Claire Brierley, Kais Dukes, Majdi Sawalha, Abdul-Baquee Sharaf I-AIBS Institute for Artificial Intelligence and Biological Systems School of Computing, University of Leeds

41 Questions?


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