tailieunhanh - Báo cáo khoa học: "Tagging Urdu Text with Parts of Speech: A Tagger Comparison"

In this paper, four state-of-art probabilistic taggers . TnT tagger, TreeTagger, RF tagger and SVM tool, are applied to the Urdu language. For the purpose of the experiment, a syntactic tagset is proposed. A training corpus of 100,000 tokens is used to train the models. Using the lexicon extracted from the training corpus, SVM tool shows the best accuracy of . After providing a separate lexicon of 70,568 types, SVM tool again shows the best accuracy of . | Tagging Urdu Text with Parts of Speech A Tagger Comparison Hassan Sajjad Universitat Stuttgart Stuttgart. Germany sajjad@ Helmut Schmid Universitat Stuttgart Stuttgart Germany schmid@ Abstract In this paper four state-of-art probabilistic taggers . TnT tagger TreeTagger RF tagger and SVM tool are applied to the Urdu language. For the purpose of the experiment a syntactic tagset is proposed. A training corpus of 100 000 tokens is used to train the models. Using the lexicon extracted from the training corpus SVM tool shows the best accuracy of . After providing a separate lexicon of 70 568 types SVM tool again shows the best accuracy of . 1 Urdu Language Urdu belongs to the Indo-Aryan language family. It is the national language of Pakistan and is one of the official languages of India. The majority of the speakers of Urdu spread over the area of South Asia South Africa and the United King-dom1. Urdu is a free order language with general word order SOV. It shares its phonological morphological and syntactic structures with Hindi. Some linguists considered them as two different dialects of one language Bhatia and Koul 2000 . However Urdu is written in Perso-arabic script and inherits most of the vocabulary from Arabic and Persian. On the other hand Hindi is written in Devanagari script and inherits vocabulary from Sanskrit. Urdu is a morphologically rich language. Forms of the verb as well as case gender and number are expressed by the morphology. Urdu represents case with a separate character after the head noun of the noun phrase. Due to their separate occurrence and their place of occurrence they are sometimes considered as postpositions. Considering them as case markers Urdu has no minative ergative accusative dative instrumental genitive and locative cases Butt 1995 pg 10 . The Urdu verb phrase contains a main verb a light verb describing the aspect and a tense verb describing the tense of the phrase Hardie .

• Báo cáo khoa học
• Tagging Urdu Text
• Parts of Speech
• A Tagger Comparison
• scientific reports
• model language
• process natural language
• Dialog Control
• Natural Language System
• Dialog Control in a Natural Language System
• Expanding the Horizons
• Natural Language Interfaces
• Phil Hayes
• PROSPECTS OR PRACTICAL
• NATURAL LANGUAGE SYSTEMS
• Workshops
• NATURAL LANGUAGE
• INTERACTION WITH MACHINES
• Long Papers
• COMPUTER INTEBFACE DESIGN MURRAY TUROFF DEPARTMENT OF COMPUTER
• IiVFORMATION SCIENCE IIEW JERSEY INSTITUTE OF TECHNOLOGY
• EVALUATION OF NATURAL LANGUAGE
• INTERFACES TO DATABASE SYSTEMS
• A PANEL DISCUSSION
• database query system
• J
• Norwood Crout
• INTERFACES TO DATA BASE SYSTEMS
• Bozena Henisz
• INTERPRETING NATURAL LANGUAGE
• DATABASE UPDATES
• S
• Jermld Kaplan Jim David
• TRANSPORTABLE NATURAL LANGUAGE
• INTERFACES TO DATABASES
• Gary G
• Hendrlx and William H
• Lewis
• DATABASES THEORETICAL
• TECHNICAL ISSUES
• TRANSPORTABLE NATURAL LANGUAGE INTERFACES
• PROBLEMS AND TECHNIQUES
• Barbara J
• Grosz
• THEORETICAL TECHNICAL ISSUES
• NATURAL LANGUAGE ACCESS TO DATABASES
• R
• Petrick
• Domain Independent
• Database Access Systems
• ISSUES IN NATURAL LANGUAGE
• ACCESS TO DATABASES
• A LOGIC PROGRAMMING PERSPECTIVE
• Sharon C
• Salveter David Maier
• PLANNING NATURAL LANGUAGE
• EXPRESSIONS REFERRING
• Douglas E
• Appelt
• THE TEXT SYSTEM
• NATURAL LANGUAGE GENERATION
• Kathleen R
• M
• MENTING A DATABASE
• KNOWLEDGE REPRESENTATION
• THE KEY TO THE SELECTION PROBLEM
• E
• Jeffrey Conklin David D
• McDonald
• A KNOWLEDGE ENGINEERING
• NATURAL LANGUAGE UNDERSTANDING
• Stuart C
• Shapiro
• NATURAL LANGUAGE TEXTS
• NECESSARILY GRAMMATICAL
• EVEN COMPLETE
• UNGRAMHATICALITY
• EXTRA GRAMMATICALITY
• NATURAL LANGUAGE UNDERSTANDING SYSTEMS
• Taxonomy
• Descriptions
• Individuals in Natural
• Language Understanding
• The Use of Ooject Special Knowledge
• Natural Language Processing
• Mark H
• Bursteln