tailieunhanh - Báo cáo khoa học: "MOVEMENT IN ACTIVE PRODUCTION NETWORKS"

We describe how movement is handled in a class of computational devices called active production networks (APNs). The APN model is a parallel, activation-basod framework that ha= been applied to other aspects of natural language processing. The model is briefly defined, the notation and mechanism for movement is explained, and then several examples are given which illustrate how various conditions on movement can naturally be explained in terms of limitations of the APN device. I. | MOVEMENT IN ACTIVE PRODUCTION NETWORKS Mark A. Jones Alan s. Driscoll AT T Bell Laboratories Murray Hill. New Jersey 07974 ABSTRACT We describe how movement is handled in a class of computational devices called active production networks APNs . The APN model is a parallel activation-based framework that has been applied to other aspects of natural language processing. The model is briefly defined the notation and mechanism for movement is explained and then several examples are given which illustrate how various conditions on movement can naturally be explained in terms of limitations of the APN device. 1. INTRODUCTION Movement is an important phenomenon in natural languages. Recently proposals such as Gazdar s derived rules Gazdar 1982 and Pereira s extraposition grammars Pereira 1983 have attempted to find minimal extensions to the context-free framework that would allow the description of movement. In this paper we describe a class of computational devices for natural language processing called active production networks APNi and explore how certain kinds of movement are handled. In particular we are concerned with left extraposition such as Subjectauxiliary Inversion Wk-movement and NP holes in relative clauses. In these cases the extraposed constituent leaves a trace which is inserted at a later point in the processing. This paper builds on the research reported in Jones 1983 and Jones forthcoming . 2. ACTIVE PRODUCTION NETWORKS 11 The Device Our contention is that only a class of parallel devices will prove to be powerful enough to allow broad contextual priming to pursue alternative hypotheses and to explain the paradox that the performance of a sequential system often degrades with new knowledge whereas human performance usually improves with learning and 2 There are a number of new parallel processing connection-ist models which are sympathetic to this view Anderson 1983 Feldman and Ballard 1982 Waltz and Pollack 1985 . McClelland and .

• Báo cáo khoa học
• MOVEMENT IN ACTIVE
• PRODUCTION NETWORKS
• 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