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Cohesion, Coherence and Temporal Reference from an Experimental Corpus Pragmatics Perspective.

Bibliographic Details
Main Author: Grisot, Cristina.
Format: eBook
Language:English
Published: Cham : Springer International Publishing AG, 2018.
Edition:1st ed.
Series:Yearbook of Corpus Linguistics and Pragmatics Series
Subjects:
Electronic books.
Online Access:Click to View
Table of Contents:
  • Intro
  • Acknowledgements
  • Introduction
  • Contents
  • List of Figures
  • List of Tables
  • Chapter 1: The Linguistic Expression of Temporal Reference
  • 1.1 Verbal Tenses in English and Romance Languages
  • 1.1.1 The Simple Past
  • 1.1.2 The Imperfect
  • 1.1.3 The Compound Past
  • 1.1.4 The Present
  • 1.2 Temporal Cohesive Ties
  • 1.2.1 Tense
  • 1.2.2 Aktionsart
  • 1.2.3 Aspect
  • 1.3 Summary
  • Chapter 2: Formal Semantic-Discursive and Pragmatic Assessments of Temporal Reference
  • 2.1 The Formal Semantic-Discursive Account
  • 2.2 The Gricean Account
  • 2.3 The Relevance-Theoretic Account
  • 2.3.1 Basic Relevance-Theoretic Tenets
  • 2.3.2 The Conceptual/Procedural Distinction
  • 2.3.3 Verbal Tenses as Procedural Expressions: Reichenbachian Coordinates
  • 2.3.4 Verbal Tenses as Procedural Expressions: Temporal Relations
  • 2.4 Summary
  • Chapter 3: Corpus-Based Contrastive Study of Verbal Tenses
  • 3.1 Dealing with Corpus Data
  • 3.2 Bilingual Corpus: English-French
  • 3.2.1 Monolingual Analysis
  • 3.2.2 Cross-Linguistic Analysis
  • 3.3 Bilingual Corpus: French-English
  • 3.3.1 Monolingual Analysis
  • 3.3.2 Cross-Linguistic Analysis
  • 3.4 Multilingual Corpus
  • 3.4.1 Data Collection
  • 3.4.2 Analysis and Results
  • 3.5 Summary
  • Chapter 4: Experimental Study Using Annotation Experiments
  • 4.1 Dealing with Annotation Data: Inter-annotator Agreement and the Қ Coefficient
  • 4.2 Annotation Experiments with Tense and Its Description Using Reichenbachian Coordinates
  • 4.2.1 Hypotheses and Predictions
  • 4.2.2 French Verbal Tenses and Reichenbachian Coordinates
  • 4.2.3 Passé Composé, Passé Simple, Imparfait and the [±Narrativity] Feature
  • 4.2.4 The Imparfait and the [±Narrativity] Feature
  • 4.2.5 Passato Prossimo, Passato Remoto, Imperfetto and the [±Narrativity] Feature.
  • 4.2.6 Perfectul Compus, Perfectul Simplu, Imperfectul and the [±Narrativity] Feature
  • 4.2.7 The Simple Past and the [±Narrativity] Feature
  • 4.3 Annotation Experiments with Aspect and Aktionsart
  • 4.3.1 Hypotheses and Predictions
  • 4.3.2 The Simple Past and the [±Boundedness] Feature
  • 4.3.3 The Simple Past and the [±Perfectivity] Feature
  • 4.4 A Generalized Mixed Model with Tense, Aspect and Aktionsart
  • 4.5 Summary
  • Chapter 5: A Pragmatic Model of Temporal Cohesive Ties
  • 5.1 The Highly Discriminatory Model of Temporal Reference
  • 5.2 Tense: A Mixed Conceptual-Procedural Temporal Category
  • 5.2.1 The Notion of Context
  • 5.2.2 Reichenbachian Coordinates: E and S
  • 5.2.3 [±Narrativity] and Reichenbachian R
  • 5.3 Aktionsart and Aspect
  • 5.4 Revisiting Verbal Tenses According to the HD Model
  • 5.4.1 Conceptual Information
  • 5.4.2 Procedural Information
  • 5.4.3 Aspect and Aktionsart
  • 5.5 Summary
  • Chapter 6: Temporal Coherence
  • 6.1 Coherence Relations
  • 6.2 The Cognitive Status of Temporal Relations
  • 6.3 Experimental Study on Processing Implicit and Explicit Sequential Relations
  • 6.3.1 "Ensuite" and "Puis" as Temporal Connectives
  • 6.3.2 Hypotheses and Predictions
  • 6.3.3 "Ensuite", the Passé Composé and Undetermined Temporal Relations: A Self-Paced Reading Experiment
  • 6.3.4 "Ensuite", the Passé Composé, the Passé Simple and Sequential Temporal Relations
  • 6.3.5 "Puis", the Passé Composé, the Passé Simple and Sequential Temporal Relations
  • 6.3.6 "Ensuite" and "Puis"-Mixed Statistical Analysis
  • 6.4 What Is "Cognitive Temporal Coherence"?
  • 6.4.1 Temporal Cohesion Ties Are Cognitively Motivated
  • 6.4.2 Coherent Mental Representations
  • 6.5 Summary
  • Chapter 7: Application to Natural Language Processing and Machine Translation
  • 7.1 Temporal Cohesion Ties and Automatic Processing of Language.
  • 7.1.1 Natural Language Processing
  • 7.1.2 Machine Translation
  • 7.2 The Automatic Classification of [±narrativity] and [±boundedness]
  • 7.2.1 Automatic Annotation Experiments
  • 7.2.1.1 Annotation of the [±narrativity] Feature
  • 7.2.1.2 Annotation of the [±boundedness] Feature
  • 7.2.2 Machine Translation Experiments
  • 7.2.2.1 MT Experiments with the [±narrativity] Feature
  • 7.2.2.2 MT Experiments with the [±boundedness] Feature
  • 7.3 Summary
  • Conclusion
  • Appendix: Description of the Corpora and Their Sources
  • References
  • Index.

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