TAILIEUCHUNG - Báo cáo khoa học: "CODES AND CLUES IN CONTEXTS"

Some of the meaning of a discourse is encoded in its linguistic forms. Thls is the truth-conditional meaning of the propositions those forms express and entail. Some of the meaning is suggested (or 'implicated', as Grice would say) by the fact that the encooer expresses just those propositions in just those linguistic forms in just the given contexts [ 2 ] . The first klnd of meaning is usually labeled 'semantics'; it is decoded. The second Is usually labeled 'pragmatlcs'; it is inferred from clues provided by code and context. Both kinds of meaning are related to syntax in. | DISCOURSE CODES AND CLUES IN CONTEXTS Jane J. Robinson Artificial Intelligence Center SRI International Menlo Park California Some of the meaning of a discourse Is encoded In Its linguistic forms. This Is the truth-conditional meaning of the propositions those forms express and entail. Some of the meaning is suggested or Implicated as Grice would say by the fact that the encoder expresses Just those propositions In Just those linguistic forms In Just the given contexts 2 . The first kind of meaning Is usually labeled semantics It Is decoded. The second Is usually labeled pragmatics It Is Inferred from clues provided by code and context. Both kinds of meaning are related to syntax In ways that we are coming to understand better as work continues In analyzing language and constructing processing models for communication. We are also coming to a better understanding of the relationship between the perceptual and conceptual structures that organize human experience and make it encodable In words. Cf. 1 4 . I see this progress In understanding not as the result of a revolution In the paradigm of computational linguistics In which one approach to natural language processing 13 abandoned for another but rather as an expansion of our Ideas of what both language and computers can do. We have been able to incorporate what we learned earlier In the game In a broader approach to more significant tasks. Certainly within the last twenty years the discipline of computational linguistics has expanded Its view of Its object of concern. Twenty years ago that view was focussed on a central aspect of language language as code 3 . The paradigmatic task of our discipline then was to transform a message encoded In one language Into the same message encoded In another using dictionaries and syntactic rules. Originally the task was not to translate but to transform the Input as an aid to human translators. Coincidentally those were the days of batch processing and the typical Inputs were .

• Báo cáo khoa học
• CODES AND CLUES IN CONTEXTS
• Jane J
• Robinson
• Workshops
• 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
• 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