TAILIEUCHUNG - Báo cáo khoa học: "Rule-based Acquisition and Maintenance Lexical and Semantic Knowledge"

The lexicons for Knowledge-Based Machine Translation systems require knowledge intensive morphological, syntactic and semantic information. This information is often used in different ways and usually formatted for a specific NLP system. This tends to make both the acquisition and maintenance of lexical databases cumbersome, inefficient and error-prone. In order to solve these problems, we have developed a program called COOL which automates the acquisition and maintenance processes and allows us to standardize and centralize the databases. . | Rule-based Acquisition and Maintenance of Lexical and Semantic Knowledge Donna M. Gates and Peter Shell Internet dmg@ pshell@ Center for Machine Translation Carnegie Mellon University 5000 Forbes Avenue Pittsburgh PA 15213 . Abstract The lexicons for Knowledge-Based Machine Translation systems require knowledge intensive morphological syntactic and semantic information. This information is often used in different ways and usually formatted for a specific NLP system. This tends to make both the acquisition and maintenance of lexical databases cumbersome inefficient and error-prone. In order to solve these problems we have developed a program called COOL which automates the acquisition and maintenance processes and allows US to standardize and centralize the databases. This system is currently being used in the ESTRATO machine translation project at the Center for Machine Translation. 1 Introduction In this paper we describe a fully-implemented rulebased system for the semi-automatic acquisition and maintenance of lexical and semantic knowledge in a knowledge-based machine translation system. This rule-based system is called COOL creator of ontologies and Lexicons. COOL can create and update various lexical and semantic knowledge sources for different NLP modules. COOL is a working system that was developed for ESTRATO EScae a de TRAductores de Toledo a joint project of the Center for Machine Translation at CMU and Union Electrica Fenosa an electric utility company in Madrid Spain. ESTRATO is a system This project was funded by Union Electrica Fenosa Madrid Spain. for translating Spanish to English in a restricted domain with controlled input. ESTRATO consists of several modules from the KANT MT system Mitamura et al. 1991 as well as morphological analysis and phrasal recognition modules and the TWS authoring environment Nirenburg et al. 1992 . As shown in figure 1 every ESTRATO run-time module uses a different lexical or semantic knowledge source

• Báo cáo khoa học
• Rule based Acquisition
• Maintenance Lexical
• Semantic Knowledge
• 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