Lexical Semantics and Knowledge Representation in Multilingual Text Generation

1999
ISBN: 978-0-7923-8419-9
Verlag: Springer US

Buch, Englisch, Band 492, 219 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 1140 g

Reihe: The Springer International Series in Engineering and Computer Science

In knowledge-based natural language generation, issues of formal knowledge representation meet with the linguistic problems of choosing the most appropriate verbalization in a particular situation of utterance. presents a new approach to systematically linking the realms of lexical semantics and knowledge represented in a description logic. For language generation from such abstract representations, lexicalization is taken as the central step: when choosing words that cover the various parts of the content representation, the principal decisions on conveying the intended meaning are made. A preference mechanism is used to construct the utterance that is best tailored to parameters representing the context.
develops the means for systematically deriving a set of paraphrases from the same underlying representation with the emphasis on events and verb meaning. Furthermore, the same mapping mechanism is used to achieve multilingual generation: English and German output are produced in parallel, on the basis of an adequate division between language-neutral and language-specific (lexical and grammatical) knowledge.
provides detailed insights into designing the representations and organizing the generation process. Readers with a background in artificial intelligence, cognitive science, knowledge representation, linguistics, or natural language processing will find a model of language production that can be adapted to a variety of purposes.

Zielgruppe

Research

Autoren/Hrsg.

Stede, Manfred

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Natürliche Sprachen & Maschinelle Übersetzung
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Geisteswissenschaften Sprachwissenschaft Computerlinguistik, Korpuslinguistik

Inhaltsverzeichnis

1. Introduction.- 1.1 Natural language generation.- 1.2 Goals of this research.- 1.3 Overview of the book.- 2. Lexicalization in NLG.- 2.1 Introduction.- 2.2 The nature of lexical items in NLP.- 2.3 Linking concepts to lexical items.- 2.4 Criteria for lexical choice.- 2.5 Placing lexicalization in the generation process.- 2.6 Conclusions: making progress on lexicalization.- 3. Classifying Lexical Variation.- 3.1 Intra-lingual paraphrases.- 3.2 Inter-lingual divergences.- 3.3 Divergences as paraphrases.- 4. Modelling the Domain.- 4.1 Building domain models for NLG.- 4.2 Knowledge representation in LOOM.- 4.3 Ontological categories.- 4.4 The domain model.- 5. Levels of Representation: Sitspec and Semspec.- 5.1 Finding appropriate representation levels in NLG.- 5.2 Linguistic ontology: adapting the ‘Upper Model’.- 5.3 SitSpecs.- 5.4 SemSpecs.- 6. Representing the Meaning of Words.- 6.1 Introduction: Lexical semantics.- 6.2 Denotation and covering.- 6.3 Partial SemSpecs.- 6.4 Connotation.- 6.5 Salience.- 7. Verb Alternations and Extensions.- 7.1 Background: verb alternations.- 7.2 Alternations as meaning extensions.- 7.3 Lexical rules for alternations and extensions.- 7.4 Extension rules for circumstances.- 7.5 Examples: lexical entries for verbs.- 7.6 Summary.- 8. A System Architecture for Multilingual Generation.- 8.1 Lexicalization with constraints and preferences.- 8.2 The computational problem.- 8.3 Architecture and algorithm.- 8.4 Implementation: MOOSE.- 8.5 Summary: lexicalization qua subsumption.- 9. Generating Paraphrases.- 9.1 Verbalizing states.- 9.2 Verbalizing activities.- 9.3 Verbalizing events.- 9.4 Solutions to legalization problems.- 10. From Sentences to Text.- 10.1 Text representation.- 10.2 Embedding MOOSE in a text generator.- 10.3 Example:technical documentation.- 11. Summary and Conclusions.- 11.1 Summary of the work.- 11.2 Comparison to related work.- 11.3 Directions for future research.- References.