Teleology and the norms of nature:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York [u.a.]
Garland
2000
|
| Schriftenreihe: | Studies in philosophy
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XI, 390 S. |
| ISBN: | 0815336020 |
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Datensatz im Suchindex
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|---|---|
| adam_text |
Natural Language Processing and
Knowledge Representation
Language for Knowledge
and Knowledge for Language
Editedby
Lucja M Iwatiska and Stuart C Shapiro
AMI PRESS / THE MIT PRESS
MENLO PARK, CALIFORNIA, CAMBRIDGE, MASSACHUSETTS, LONDON, ENGLAND
Contents
Preface / xiii
Lucja M Iwanska and Stuart C Shapiro
Contributors / xix
Section One
Formal, Computational, Representations and
Inference Methods Based on Natural Language
Section Introduction / 3
Lucja M Iwanska and Stuart C Shapiro
Chapter One
Natural Language Is a Powerful Knowledge
Representation System: The UNO Model / 7
Lucja M Iwanska
This chapter presents a novel view of natural language as a powerful, general-purpose knowl-
edge representation system particularly suitable for handling knowledge in not well formalized
domains It discusses a number of highly desirable representational and inferential characteris-
tics unique to natural language They include great expressiveness combined with computation-
al tractabiliry, rich structure, exploitation of logical contradiction and logical redundancy, in-
herent underspecificity and context-dependency, and facilitating learning A formal
computational model of natural language that closely simulates these characteristics is present-
ed Many examples illustrate the computational mechanism of representing and reasoning with
meaning of natural language and different types of knowledge, including taxonomic, probabilis-
tic, temporal and some aspects of spatial knowledge A large-scale implementation of the model
is also discussed The system allows one to automatically acquire and utilize knowledge from
large-scale corpora of textual documents
Chapter Two
Natural Language Syntax and First Order Inference / 65
David A McAUester and Robert Givan
The authors have argued elsewhere that first order inference can be made more efficient by using
nonstandard syntax for first order logic In this chapter, they define a syntax for first order logic
based on the structure of natural language under Montague semantics They show that, for a
certain fairly expressive fragment of this language, satisfiability is polynomial time decidable
The polynomial time decision procedure can be used as a subroutine in general purpose infer-
ence systems and seems to be more powerful than analogous procedures based on either classi-
cal or taxonomic syntax
viii CONTENTS
Chapter Three
Issues in the Representation of Real Texts: The Design of KRISP / 77
David D McDonald
Attempting to understand a journalist's real texts puts special demands on the formalism that a
language comprehension system uses to represent what it has understood KRISP is an experi-
mental representation system that was designed to address these demands: high-speed opera-
tion, the ability to accommodate a very wide range of grammatical constructions, and reversibil-
ity Its fundamental motivations stem from investigations over the course of the last decades to
try and establish just why it was that other representational systems were always turning out to
be awkward when used as the source for the generation of fluent prose Formally, KRISP is essen-
tially an object-oriented repackaging of a typed lambda calculus, paying particular attention to
the representation of partially saturated relations and providing first class objects to represent
the binding of a variable to a value As a representational system, it embodies a theory of how
information is structured in a natural language text This is a hypothesis about the nature of the
objects that texts denote and the principles of semantic interpretation that map them to a model
comprised of such objects It is intended to run in close coordination with the SPARSER natural
language understanding system
Chapter Four
Episodic Logic Meets Little Red Riding Hood—A Comprehensive
Natural Representation for Language Understanding /111
Lenhart K Schubert and Chung Hee Hwang
The authors describe a comprehensive framework for narrative understanding based on episod-
ic logic This situational logic was developed and implemented as a semantic representation and
commonsense knowledge representation that would serve the full range of interpretive and in-
ferential needs of general natural language understanding The most distinctive feature of
episodic logic is its natural languagelike expressiveness It allows for generalized quantifiers,
lambda abstraction, sentence and predicate modifiers, sentence and predicate teification, inten-
sional predicates (corresponding to wanting, believing, making, etc ), unreliable generalizations,
and perhaps most importantly, explicit situational variables linked to arbitrary formulas that
describe them These allow episodes to be explicitly related in terms of part-whole, temporal
and causal relations Episodic logical form is easily computed from surface syntax and lends it-
self to effective inference
Chapter Five
SNePS: A Logic for Natural Language Understanding
and Commonsense Reasoning / 175
Stuart G Shapiro
The use of logic for knowledge representation and reasoning systems is controversial There are,
indeed, several ways that standard first order predicate logic is inappropriate for modeling nat-
ural language understanding and commonsense reasoning However, a more appropriate logic
can be designed This chapter presents several aspects of such a logic
Section Two
Knowledge Representation and Acquisition for Large-Scale,
General-Purpose Natural Language Processing Systems
Section Introduction / 193
Lucja M Iwanska and Stuart C Shapiro
CONTENTS ix
Chapter Six
A Multi-Level Approach to Interlingual Machine Translation:
Defining the Interface between Representational Languages / 207
Bonnie ] Dorr and Clare R Voss
This chapter describes a multi-level design, ie,a nonuniform approach to interlingual machine
translation, in which distinct representational languages are used for different types of knowl-
edge The authors demonstrate that a linguistically-motivated division of labor across multi-
ple representation levels has not complicated, but rather has readily facilitated, the identification
and construction of systematic relations at the interface between each level They describe a
model of interpretation and representation of natural language sentences that has been imple-
mented as part of an interlingual machine-translation system called PRINCITRAN
Chapter Seven
Uniform Natural (Language) Spatio-Temporal Logic: Reasoning about
Absolute and Relative Space and Time / 249
Lucja M Iwanska
In this chapter, uniform spatio-temporal reasoner is presented Its representational, inferential
and computational characteristics closely resemble natural language It is demonstrated that im-
portant inferences about time and space can be captured by a general representation and reason-
ing mechanism inherent in natural language many aspects of which are closely mimicked by the
proposed computational model of natural language As a result, a uniform representation and
inference, and therefore a simple architecture, for temporal, spatial and other reasoning is ac-
complished It is also shown that computing logical, context-independent and some nonmono-
tonic, context-dependent inferences for temporal, spatial and other objects is analogous
Real-life examples illustrate the representational and reasoning capabilities of the proposed
natural language style spatio-temporal reasoner, including many previously unaccounted as-
pects of temporal and spatial information conveyed by common English temporal expressions,
reasoning with information from arbitrary Boolean temporal expressions involving explicit
negation, disjunction and conjunction, handling temporal quantifiers, handling infinite number
of temporal and spatial relations, handling both absolute and relative temporal and spatial in-
formation, and handling nonnumeric qualitative temporal and spatial information
Chapter Eight
Mixed Depth Representations for Dialog Processing / 283
Susan W McRoy, Syed S Ali, and Susan M Hatter
The authors describe their work on developing a general purpose tutoring system that will allow
students to practice their decision-making skills in a number of domains The tutoring system,
B2, supports mixed-initiative natural language interaction The natural language processing and
knowledge representation components are also general purpose—which leads to a tradeoff be-
tween the limitations of superficial processing and syntactic representations and the difficulty of
deeper methods and conceptual representations Their solution uses a mixed-depth representa-
tion, one that encodes syntactic and conceptual information in the same structure As a result,
they can use the same representation framework to produce a detailed representation of re-
quests and to produce a partial representation of questions Moreover, the representations use
the same knowledge representation framework that is used to reason about discourse processing
and domain information—so that the system can reason with (and about) the utterances, if nec-
essary This work is the first (and to our knowledge, the only) implementation of mixed-depth
representations for dialog processing
x CONTENTS
Chapter Nine
Enriching the WordNet Taxonomy with
Contextual Knowledge Acquired from Text / 301
Sanda M Harabagiu and Dan I Moldovan
This chapter presents a possible solution for the problem of integrating contextual knowledge
in the WordNet database Contextual structures are derived from three sources: (1) minimal
contexts—in the form of semantic net transformations of WordNet glosses; (2) dynamic con-
texts rendered by webs of lexico-semantic paths revealing textual implied information and (3)
static contexts—represented by patterns of concepts and semantic links The relevance of these
structures is measured on a three-tired benchmark, comprising word-sense disambiguation,
conference resolution, and acquisition of domain patterns for information extraction
Chapter Ten
Fully Automatic Acquisition of Taxonomic Knowledge from Large
Corpora of Texts: Limited-Syntax Knowledge Representation System
based on Natural Language / 335
Lucja M Iwanska, Naveen Mata, and Kellyn Kruger
This chapter presents a new method for fully automatic knowledge acquisition from large cor-
pora of unseen texts The approach exploits simple, efficiently, fast and reliably extractable,
parsable and in-depth interpretable constructs of'natural language specialized to convey taxo-
nomic knowledge It allows one to acquire large quantities of high quality general-purpose
knowledge and practically eliminates costly and error-prone human pre amp;post-processing Ex-
amples of the system-acquired concepts are discussed
Chapter Eleven
A Computational Theory of Vocabulary Acquisition / 347
William ] Rapaport and Karen Ehrlich
As part of an interdisciplinary project to develop a computational cognitive model of a reader
of narrative text, the authors are developing a computational theory of how natural-language-
understanding systems can automatically acquire new vocabulary by determining from context
the meaning of words that are unknown, misunderstood, or used in a new sense Context in-
cludes surrounding text, grammatical information, and background knowledge, but no external
sources The authors' thesis is that the meaning of such a word can be determined from context,
can be revised upon further encounters with the word, converges to a dictionarylike definition
if enough context has been provided and there have been enough exposures to the word, and
eventually settles down to a steady state that is always subject to revision upon further encoun-
ters with the word The system is being implemented in the SNePS knowledge-representation
and reasoning system
Appendices
Appendix A
Propositional, First-Order, and Higher-Order Logics / 379
Stuart C Shapiro
Appendix B
Relations, Lattices, Algebras, Generalized Quantifier:
Definitions and Theorems / 397
Lucja M Iwanska
CONTENTS xi
Appendix C
Representational and Inferential Challenges of
Natural Language : Examples and Data / 403
Lucja M Iwanska
Bibliography / 415
Index / 441 |
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| spelling | Fitzpatrick, William John 1830-1895 Verfasser (DE-588)137984847 aut Teleology and the norms of nature William J. FitzPatrick New York [u.a.] Garland 2000 XI, 390 S. txt rdacontent n rdamedia nc rdacarrier Studies in philosophy Teleologie (DE-588)4059367-8 gnd rswk-swf Ethik (DE-588)4015602-3 gnd rswk-swf Philosophie (DE-588)4045791-6 gnd rswk-swf Biologie (DE-588)4006851-1 gnd rswk-swf Teleologie (DE-588)4059367-8 s Ethik (DE-588)4015602-3 s Biologie (DE-588)4006851-1 s Philosophie (DE-588)4045791-6 s DE-604 HEBIS Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008976568&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Fitzpatrick, William John 1830-1895 Teleology and the norms of nature Teleologie (DE-588)4059367-8 gnd Ethik (DE-588)4015602-3 gnd Philosophie (DE-588)4045791-6 gnd Biologie (DE-588)4006851-1 gnd |
| subject_GND | (DE-588)4059367-8 (DE-588)4015602-3 (DE-588)4045791-6 (DE-588)4006851-1 |
| title | Teleology and the norms of nature |
| title_auth | Teleology and the norms of nature |
| title_exact_search | Teleology and the norms of nature |
| title_full | Teleology and the norms of nature William J. FitzPatrick |
| title_fullStr | Teleology and the norms of nature William J. FitzPatrick |
| title_full_unstemmed | Teleology and the norms of nature William J. FitzPatrick |
| title_short | Teleology and the norms of nature |
| title_sort | teleology and the norms of nature |
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| topic_facet | Teleologie Ethik Philosophie Biologie |
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