tailieunhanh - Báo cáo khoa học: "EXPLOITING CONVERSATIONAL IMPLICATURE FOR GENERATING CONCISE EXPLANATIONS"

This paper presents an approach for achieving conciseness in generating explanations, which is clone by exploiting formal reconstructions of aspects of the Gricean principle of relevance to simulate conversational implicature. By applying contextually motivated inference rules in an anticipation feed-back loop, a set of propositions explicitly representing an explanation's content is reduced to a subset which, in the actual context, can still be considered to convey the message adequately. | EXPLOITING CONVERSATIONAL IMPLICATURE FOR GENERATING CONCISE EXPLANATIONS HELMUT HORACEK Universitat Bielefeld Fakultat fiiir Linguistik und Literaturwissenschaft Postfach 8640 D-4800 Bielefeld 1 Deutschland ABSTRACT This paper presents an approach for achieving conciseness in generating explanations which is done by exploiting formal reconstructions of aspects of the Gricean principle of relevance to simulate conversational implicature. By applying contextually motivated inference rules in an anticipation feed-back loop a set of propositions explicitly representing an explanation s content is reduced to a subset which in the actual context can still be considered to convey the message adequately. 1. INTRODUCTION The task of providing informative natural language explanations for illustrating the results produced by decision support systems has been given increased attention recently. The proposed methods preferably address tailoring of explanations to the needs of theữ addressees including for instance object descriptions 8 and presentation of taxonomic knowledge 7 . In addition particular emphasis has been put on reactive explanation techniques for selecting an appropriate content according to contextual interpretation 6 and on the way of presenting explanations by taking the information seeking person s knowledge into account 1 . Whereas these approaches attack various issues important for the generation of natural language explanations none of them has focussed on the conciseness of explanations in a broader context. Aiming at the production of natural and concise texts we have concentrated our efforts on presenting different types of knowledge and their inteưelations because this kind of information is typically relevant for explanations. We formally reconstruct aspects of the Gricean principle of relevance 3 and exploit the results obtained for creating concise explanations to questions about solutions proposed by the expert system OFFICE-PLAN 5 . This system

• Báo cáo khoa học
• EXPLOITING CONVERSATIONAL IMPLICATURE
• HELMUT HORACEK
• GENERATING CONCISE EXPLANATIONS
• 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