TAILIEUCHUNG - Báo cáo khoa học: "A STOCHASTIC APPROACH TO SENTENCE PARSING"

A description will be given of a procedure to asslgn the most likely probabilitles to each of the rules of a given context-free grammar. The grammar developed by S. Kuno at Harvard University was picked as the basis and was successfully augmented with rule probabilities. A brief exposition of the method with some preliminary results, w h e n u s e d as a device for disamblguatingparsing English texts picked from natural corpus, will be given. | A STOCHASTIC APPROACH TO SENTENCE PARSING Tetsunosuke Fujisaki Science Institute IBM Japan Ltd. No. 36 Kowa Building 5-19 Sanbancho Chiyoda-ku Tokyo 102 Japan ABSTRACT A description will be given of a procedure to assign the most likely probabilities to each of the rules of a given context-free grammar. The grammar developed by s. Kuno at Harvard University was picked as the basis and was successfully augmented with rule probabilities. A brief exposition of the method with some preliminary results when used as a device for disambiguating parsing English texts picked from natural corpus will be given. I. INTRODUCTION To prepare a grammar which can parse arbitrary sentences taken from a natural corpus is a difficult task. One of the most serious problems is the potentially unbounded number of ambiguities. Pure syntactic analysis with an imprudent grammar will sometimes result in hundreds of parses. With prepositional phrase attachments and conjunctions for example it is known that the actual growth of ambiguities can be approximated by a Cat-lan number Knuth the number of ways to insert parentheses into a formula of N terms 1 2 5 14 42 132 469 1430 4892 . The five ambiguities in the following sentence with three ambiguous constructions can be well explained with this number. I saw a man in a park with a scope. This Catalan number Is essentially exponential and Martin reported a syntactically ambiguous sentence with 455 parses List the sales of products produced in 1973 with the products produced In 1972. On the other hand throughout the long history of natural language understanding work semantic and pragmatic constraints are known to be Indispensable and are recommended to be represented in some formal way and to be referred to during or after the syntactic analysis process. However to represent semantic and pragmatic constraints which are usually domain sensitive in a well-formed way is a very difficult and expensive task. A lot of effort In that direction has been

• Báo cáo khoa học
• A STOCHASTIC APPROACH TO SENTENCE PARSING
• Tetsunosuke FuJisaki
• Long Papers
• 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
• 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