Representation and Management of Narrative Information

Theoretical Principles and Implementation
1. Auflage 2009
ISBN: 978-1-84800-078-0
Verlag: Springer-Verlag
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 302 Seiten

A big amount of important, 'economically relevant' information, is buried within the huge mass of multimedia documents that correspond to some form of 'narrative' description. Due to the ubiquity of these 'narrative' resources, being able to represent in a general, accurate, and effective way their semantic content - i.e., their key 'meaning' - is then both conceptually relevant and economically important. In this book, we present the main properties of NKRL ('Narrative Knowledge Representation Language'), a language expressly designed for representing, in a standardised way, the 'meaning' of complex multimedia narrative documents. NKRL is a fully implemented language/environment. The software exists in two versions, an ORACLE-supported version and a file-oriented one. Written from a multidisciplinary perspective, this exhaustive description of NKRL and of the associated knowledge representation principles will be an invaluable source of reference for practitioners, researchers, and graduates.

Autoren/Hrsg.

Inhaltsverzeichnis

1;Contents;9
2;Preface;5
3;Chapter 1 Basic Principles;11
3.1;Narrative Information in an NKRL Context;12
3.1.1;Narratology and NKRL;12
3.1.1.1;‘‘Fictional’’ and ‘‘Nonfictional’’ Narratives;13
3.1.1.2;Informal Definition of an NKRL ‘‘Narrative’’;15
3.1.2;The Notion of ‘‘Event’’ in an NKRL Context;17
3.1.2.1;A Kimian-like Analysis;18
3.1.2.2;A Davidsonian-like Analysis;20
3.1.2.3;Final Notes on the Linguistic Theories about ‘‘Events’’;22
3.2;Knowledge Representation and NKRL;23
3.2.1;‘‘Standard’’ Ontologies and the ‘‘n-ary’’ Problem;24
3.2.1.1;Introducing the n-ary Problem;24
3.2.1.2;The W3C Suggestions;27
3.2.2;A Plain ‘‘n-ary’’ Solution and Some Related Problems;31
3.2.2.1;Previous n-ary Conceptual Realizations;32
3.2.2.2;Possible Problems Affecting Existing n-ary Solutions;39
3.3;In the Guise of Winding Up;43
4;Chapter 2 The Knowledge Representation Strategy;48
4.1;Architecture of NKRL: the Four ‘‘Components’’;48
4.2;The Data Structures of the Four Components;51
4.2.1;Definitional/Enumerative Data Structures;52
4.2.1.1;General Principles of the HClass ‘‘Frames’’;52
4.2.1.2;Prototype Slots;54
4.2.1.3;Categories of Properties;57
4.2.1.3.1;‘‘Relation-type’’ Properties;58
4.2.1.3.2;‘‘Attribute-type’’ Properties;60
4.2.1.3.3;‘‘Procedure-type’’ Properties;61
4.2.1.4;NKRL Instances (Individuals);62
4.2.2;Descriptive/Factual Data Structures;64
4.2.2.1;General Format of the Descriptive/Factual Structures;65
4.2.2.2;Semantic Predicates, Roles, Templates and Occurrences;65
4.2.2.2.1;Semantic Predicates as Primitives;66
4.2.2.2.2;Introducing the NKRL Roles;68
4.2.2.2.3;The NKRL Templates and the ‘‘Catalogue’’;70
4.2.2.2.4;Deriving a Predicative Occurrence from a Template;75
4.2.2.3;Structured Arguments and the AECS Sub-language;77
4.2.2.3.1;The AECS Sub-language;77
4.2.2.4;Determiners (Attributes);79
4.2.2.4.1;Modulators;80
4.2.2.4.1.1;Temporal Modulators;80
4.2.2.4.1.2;Deontic Modulators;80
4.2.2.4.1.3;Modal Modulators;82
4.2.2.4.1.4;Concurrent Utilization of Several Modulators;82
4.2.2.4.2;Locations;84
4.2.2.4.3;Temporal Determiners (Attributes);85
4.2.2.4.3.1;NKRL, Timestamps and Intervals;89
4.2.2.4.3.2;Categories and Perspectives;91
4.3;Second-order Structures;95
4.3.1;The Completive Construction;96
4.3.2;Binding Occurrences;100
4.3.2.1;The Binding Operators;100
4.3.2.2;Priority Rule and Generalization to Templates;102
4.3.2.2.1;Correspondence between ‘‘Expansion’’ and ‘‘Binding’’ Operators;103
4.3.2.2.2;Using Template Labels within Binding Structures;104
4.3.2.3;Binding Operators and Temporal Representation;106
4.4;In the Guise of Winding Up;107
5;Chapter 3 The Semantic and Ontological Contents;111
5.1;The Organization of the HClass Hierarchy;111
5.1.1;General Notions about Ontologies;111
5.1.1.1;Ontologies, Taxonomies, and Concepts;112
5.1.1.2;The Semantic Web Solutions;113
5.1.1.2.1;A Quick Reminder of some OWL, etc. Features;114
5.1.1.2.2;Some General Remarks about the Semantic Web Solutions;117
5.1.1.3;The Search for a ‘‘Standard Upper Ontology’’;121
5.1.1.3.1;Recent SUO-like and SUO-oriented Efforts;121
5.1.1.3.2;Some Examples of Upper Level Ontologies;123
5.1.2;HClass Architecture;131
5.1.2.1;Non-sortal Concepts;134
5.1.2.1.1;The ‘‘property_’’ Concepts;134
5.1.2.1.1.1;Representing the ‘‘General Quantifier’’ Concepts;136
5.1.2.1.1.2;The ‘‘NKRL idioms’’ of the property_ type;137
5.1.2.1.2;The ‘‘pseudo_sortal_concept’’ Concepts;140
5.1.2.2;Sortal Concepts;143
5.2;The Organization of the HTemp Hierarchy;145
5.2.1;Recent Examples of ‘‘Structured’’ Ontological Systems;146
5.2.2;Main Features of Some Specific HTemp Structures;157
5.2.2.1;Behave: Templates;158
5.2.2.1.1;The Behave:HumanProperty Templates;159
5.2.2.1.2;Acting to Obtain a Given Result;161
5.2.2.1.3;The Behave:Attitude Templates;163
5.2.2.2;Exist: Templates;163
5.2.2.3;Experience: Templates;167
5.2.2.4;Move: Templates;170
5.2.2.5;Own: Templates;175
5.2.2.6;Produce: Templates;177
5.2.2.7;Receive: Templates;182
5.3;In the Guise of Winding Up;185
6;Chapter 4 The Query and Inference Procedures;190
6.1;‘‘Search Patterns’’ and Low-level Inferences;190
6.1.1;The Algorithmic Structure of Fum;192
6.1.1.1;Basic Principles;193
6.1.1.2;Unification/Filtering of Expansions;194
6.1.1.3;A Possible Extension of the AECS Query Language;199
6.1.2;Temporal Information and Indexing;201
6.1.2.1;The Three Indexing Levels;202
6.1.2.2;The Selection Algorithm;205
6.2;High-level Inference Procedures;208
6.2.1;General Remarks about Some Reasoning Paradigms;210
6.2.2;Hypothesis Rules;212
6.2.3;Transformation Rules;219
6.2.4;Integrating the Two Main Inferencing Modes of NKRL;223
6.2.4.1;Strategies for the Coordinated Inference Processing;225
6.2.4.2;The Correspondence among Variables;226
6.2.4.3;Some Examples;228
6.2.4.4;Additional Examples;235
6.2.4.5;Some Remarks about the Software Solutions;238
6.2.5;Inference Rules and Internet Filtering;241
6.3;In the Guise of Winding Up;246
7;Chapter 5 Conclusion;251
7.1;Technological Enhancements;251
7.2;Theoretical Enhancements;254
8;Appendix A;257
8.1;NKRL Software;257
8.2;The Two Versions of the Software;257
8.3;The Main Interface;258
8.4;The ‘‘Visualization’’ Modules;260
8.5;The ‘‘Construction and Management’’ Modules;261
8.6;The ‘‘Querying and Inferencing’’ Modules;267
9;Appendix B;272
9.1;Plural Entities in NKRL;272
9.2;A General Survey of the NKRL Solution;273
9.3;Quantification of Plural Sentences;277
9.4;Final Remarks;280
10;References;283
11;Index;299