TAILIEUCHUNG - Báo cáo khoa học: "Linguistic Knowledge Acquisition from Parsing Failures"

A semi-automatic procedure of linguistic knowledge acquisition is proposed, which combines corpus-based techniques with the conventional rule-based approach. The rule-based component generates all the possible hypotheses of defects which the existing linguistic knowledge might contain, when it fails to parse a sentence. The rule-based component does not try to identify the defects, but generates a set of hypotheses and the corpus-based component chooses the plausible ones among them. | Linguistic Knowledge Acquisition from Parsing Failures Masaki KIYONO and Jun-ichi TSUJII kiyono@ and tsujii@ Centre for Computational Linguistics University of Manchester Institute of Science and Technology PO Box 88 Manchester M60 1QD United Kingdom Abstract A semi-automatic procedure of linguistic knowledge acquisition is proposed which combines corpus-based techniques with the conventional rule-based approach. The rule-based component generates all the possible hypotheses of defects which the existing linguistic knowledge might contain when it fails to parse a sentence. The rule-based component does not try to identify the defects but generates a set of hypotheses and the corpus-based component chooses the plausible ones among them. The procedure will be used for adapting or re-using existing linguistic resources for new application domains. 1 Introduction While quite a number of useful grammar formalisms for natural language processing now exist it still remains a time-consuming and hard task to develop grammars and dictionaries with comprehensive coverage. It is also the case that though quite a few computational grammars and dictionaries with comprehensive coverage have been used in various application systems to re-use them for other application domains is not always so easy even if we use the same formalisms and programs such as parsers etc. We usually have to revise add and delete grammar rules and lexical entries in order to adapt them to the peculiarities of languages sublanguages of new application domains iSekine et al. 1992 Tsujii et al. 1992 Ananiadou 1990 . also a staff member of Matsushita Electric Industrial Co. Ltd. Tokyo JAPAN. Such adaptations of existing linguistic knowledge to a new domain are currently performed through rather undisciplined trial and error processes involving much human effort. In this paper we show that techniques similar to those in robust parsing of ill-formed input together with corpus-based

• Báo cáo khoa học
• Linguistic Knowledge Acquisition
• Parsing Failures
• Masaki KIYONO
• 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