tailieunhanh - Báo cáo khoa học: "The Rhetorical Parsing of Natural Language Texts"

We derive the rhetorical structures of texts by means of two new, surface-form-based algorithms: one that identifies discourse usages of cue phrases and breaks sentences into clauses, and one that produces valid rhetorical structure trees for unrestricted natural language texts. The algorithms use information that was derived from a corpus analysis of cue phrases. | The Rhetorical Parsing of Natural Language Texts Daniel Marcu Department of Computer Science University of Toronto Toronto Ontario Canada M5S 3G4 Abstract We derive the rhetorical structures of texts by means of two new surface-form-based algorithms one that identifies discourse usages of cue phrases and breaks sentences into clauses and one that produces valid rhetorical structure trees for unrestricted natural language texts. The algorithms use information that was derived from a corpus analysis of cue phrases. 1 Introduction Researchers of natural language have repeatedly acknowledged that texts are not just a sequence of words nor even a sequence of clauses and sentences. However despite the impressive number of discourse-related theories that have been proposed so far there have emerged no algorithms capable of deriving the discourse structure of an unrestricted text. On one hand efforts such as those described by Asher 1993 Lascarides Asher and Oberlander 1992 Kamp and Reyle 1993 Grover et al. 1994 and Priist Scha and van den Berg 1994 take the position that discourse structures can be built only in conjunction with fully specified clause and sentence structures. And Hobbs s theory 1990 assumes that sophisticated knowledge bases and inference mechanisms are needed for determining the relations between discourse units. Despite the formal elegance of these approaches they are very domain dependent and therefore unable to handle more than a few restricted examples. On the other hand although the theories described by Grosz and Sidner 1986 Polanyi 1988 and Mann and Thompson 1988 are successfully applied manually they are too informal to support an automatic approach to discourse analysis. In contrast with this previous work the rhetorical parser that we present builds discourse ưees for unrestricted texts. We first discuss the key concepts on which our approach relies section 2 and the corpus analysis section 3 that provides the empirical .

• Báo cáo khoa học
• The Rhetorical Parsing
• Natural Language Texts
• Daniel Marcu
• 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
• 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