tailieunhanh - Báo cáo khoa học: "A Logic of Semantic Representations for Shallow Parsing"

One way to construct semantic representations in a robust manner is to enhance shallow language processors with semantic components. Here, we provide a model theory for a semantic formalism that is designed for this, namely Robust Minimal Recursion Semantics (RMRS). We show that RMRS supports a notion of entailment that allows it to form the basis for comparing the semantic output of different parses of varying depth. | A Logic of Semantic Representations for Shallow Parsing Alexander Koller Saarland University Saarbrucken Germany koller@ Alex Lascarides University of Edinburgh Edinburgh UK alex@ Abstract One way to construct semantic representations in a robust manner is to enhance shallow language processors with semantic components. Here we provide a model theory for a semantic formalism that is designed for this namely Robust Minimal Recursion Semantics RMRS . We show that RMRS supports a notion of entailment that allows it to form the basis for comparing the semantic output of different parses of varying depth. 1 Introduction Representing semantics as a logical form that supports automated inference and model construction is vital for deeper language engineering tasks such as dialogue systems. Logical forms can be obtained from hand-crafted deep grammars Butt et al. 1999 Copestake and Flickinger 2000 but this lacks robustness not all words and constructions are covered and by design ill-formed phrases fail to parse. There has thus been a trend recently towards robust wide-coverage semantic construction . Bos et al. 2004 Zettlemoyer and Collins 2007 . But there are certain semantic phenomena that these robust approaches don t capture reliably including quantifier scope optional arguments and long-distance dependencies for instance Clark et al. 2004 report that the parser used by Bos et al. 2004 yields 63 accuracy on object extraction . the man that I met. . Forcing a robust parser to make a decision about these phenomena can therefore be error-prone. Depending on the application it may be preferable to give the parser the option to leave a semantic decision open when it s not sufficiently informed . to compute a partial semantic representation and to complete it later using information extraneous to the parser. In this paper we focus on an approach to semantic representation that supports this strategy Robust Minimal Recursion Semantics

• Báo cáo khoa học
• A Logic of Semantic Representations
• Shallow Parsing
• Alexander Koller
• 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