Representation and Inference for Natural Language: A First Course in Computational Semantics / Edition 1

Representation and Inference for Natural Language: A First Course in Computational Semantics / Edition 1

by Patrick Blackburn, Johan Bos
     
 

ISBN-10: 1575864967

ISBN-13: 9781575864969

Pub. Date: 04/06/2005

Publisher: Center for the Study of Language and Inf


How can computers distinguish the coherent from the unintelligible, recognize new information in a sentence, or draw inferences from a natural language passage? Computational semantics is an exciting new field that seeks answers to these questions, and this volume is the first textbook wholly devoted to this growing subdiscipline. The book explains the underlying…  See more details below

Overview


How can computers distinguish the coherent from the unintelligible, recognize new information in a sentence, or draw inferences from a natural language passage? Computational semantics is an exciting new field that seeks answers to these questions, and this volume is the first textbook wholly devoted to this growing subdiscipline. The book explains the underlying theoretical issues and fundamental techniques for computing semantic representations for fragments of natural language. This volume will be an essential text for computer scientists, linguists, and anyone interested in the development of computational semantics.

Product Details

ISBN-13:
9781575864969
Publisher:
Center for the Study of Language and Inf
Publication date:
04/06/2005
Series:
Center for the Study of Language and Information - Lecture Notes Series
Edition description:
New Edition
Pages:
376
Product dimensions:
6.00(w) x 9.00(h) x 0.90(d)

Table of Contents


1. First-order logic
First-order logic
Three inference tasks
A first-order model checker
First-order logic and natural language
2. Lambda calculus
Compositionality
Two experiments
The lambda calculus
Implementing lambda calculus
Grammar engineering
3. Underspecified representations
Scope ambiguities
Montague's approach
Storage methods
Hole semantics
4. Propositional inference
From models to proofs
Propositional tableaus
Implementing propositional tableau
Propositional resolution
Implementing propositional resolution
Theoretical remarks
5. First-order inference
A first-order tableau system
Unification
Free-variable tableaus
Implementing free-variable tableaus
First-order resolution
Implementing first-order resolution
Off-the-shelf theorem provers
Model building
6. Putting it all together
Baby Curt
Rugrat Curt
Clever Curt
Sensitive Curt
Scrupulous Curt
Knowledgeable Curt
Helpful Curt
A. Running the software - FAQ
B. Propositional logic
C. Automated reasoning for first-order logic

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