Iceberg Semantics for Mass Nouns and Count Nouns: A New Framework for Boolean Semantics

This document was uploaded by one of our users. The uploader already confirmed that they had the permission to publish it. If you are author/publisher or own the copyright of this documents, please report to us by using this DMCA report form.

Simply click on the Download Book button.

Yes, Book downloads on Ebookily are 100% Free.

Sometimes the book is free on Amazon As well, so go ahead and hit "Search on Amazon"

Iceberg semantics is a new framework of Boolean semantics for mass nouns and count nouns in which the interpretation of a noun phrase rises up from a generating base and floats with its base on its Boolean part set, like an iceberg. The framework is shown to preserve the attractive features of classical Boolean semantics for count nouns; the book argues that Iceberg semantics forms a much better framework for studying mass nouns than the classical theory does. Iceberg semantics uses its notion of base to develop a semantic theory of the differences between mass nouns and count nouns and between different types of mass nouns, in particular between prototypical mass nouns (here called mess mass nouns) like water and mud versus object mass nouns (here called neat mass nouns) like poultry and pottery. The book shows in detail how and why neat mass nouns pattern semantically both with mess mass nouns and with count nouns. Iceberg semantics is a compositional theory and in Iceberg semantics the semantic distinctions defined apply to noun phrases of any complexity. The book studies in depth the semantics of classifier noun phrases (like three glasses of wine) and measure noun phrases (like three liters of wine). The classical wisdom is that classifier interpretations are count. Recent literature has argued compellingly that measure interpretations are mass. The book shows that both connections follow from the basic architecture of Iceberg semantics. Audience: Scholars and students in linguistics - in particular semantics, pragmatics, computational linguistics and syntax – and neighbouring disciplines like logic, philosophy of language, and cognitive science.

Author(s): Fred Landman
Publisher: Springer
Year: 2020

Language: English

Acknowledgements
Contents
About the Author
Chapter 1: Introduction
1.1 Just Right
1.2 Section by Section
Chapter 2: Boolean Background
2.1 Boolean Algebras Lite
2.2 Appendix (For Readers with No Semantic Background)
2.3 Boolean Algebras
References
Chapter 3: Mountain Semantics
3.1 Mountain Semantics for Count Nouns
3.2 Counting in Mountain Semantics
3.3 Sharvy´s Definiteness Operation and the Pragmatics of the Null Element
3.4 Count Comparison
3.5 The Distributive Operator
3.6 Mountain Semantics for Mass Nouns and Count Nouns
References
Chapter 4: Sorting and Unsorting
4.1 Sorted Domains
4.2 The Gold Paradox
4.3 Sorting to the Limit: Homogeneity
4.4 The Supremum Argument
4.4.1 Furniture and Pavarotti´s Hair
4.4.2 On Buying Furniture
4.4.3 The Mad Wigmaker
4.4.4 Dual Perspective Intensionality
4.5 Portioning
4.6 Whither Mountain Semantics?
4.7 Problems of Unsorting
4.7.1 The Problem of Distribution
4.7.2 EXCURSUS: Rothstein 2010 (and Krifka 1989, 1995)
4.7.3 Grammatical Solutions to Distribution
References
Chapter 5: Iceberg Semantics for Count Nouns
5.1 Iceberg Semantics for Count Nouns
5.2 Distribution Sets and Cardinality
5.3 Compositionality and the Head Principle
5.4 An Example: The Three White Cats
5.5 Slandering Employees and Tuna Eating Cats
References
Chapter 6: Iceberg Semantics for Count Nouns and Mass Nouns
6.1 Count - Mass - Neat - Mess
6.1.1 Count, Mass, Neat, Mess as Base-Distinctions
6.1.2 Defining Count, Mass, Neat and Mess I-Sets
6.1.3 Count, Mass, Neat and Mess Intensions
6.1.4 The Imperative of Disjointness
6.2 Iceberg Semantics for DPs
6.3 Singular Shift
6.4 Portioning
6.5 Gillon´s Problem
References
Chapter 7: Neat Mass Nouns
7.1 Group Neutral and Sum Neutral Neat Mass Nouns
7.2 Conceptually and Contextually Disjoint Neat Mass Nouns
7.3 Neat Mass Nouns as Mass Nouns
7.4 Neat Mass Nouns as Neat Nouns
7.4.1 Atomicity
7.4.2 The Individual Classifier stuk(s) in Dutch
7.4.3 Count and Measure Comparison
7.4.4 Distributive Adjectives
References
Chapter 8: Mess Mass Nouns
8.1 Types of Mess Mass I-sets
8.1.1 Type 1: Like Time
8.1.2 Type 2: Like Salt Dissolved in Water
8.1.3 Type 3: Like Meat and Soup
8.1.4 Type 4: Like Rice
8.1.5 Type 5: Like Water
8.2 Downshifting
8.2.1 Shifting to Neat Mass
8.2.2 Types of Downshifts
8.2.3 Downshifting as a Last Resort Mechanism
8.2.4 What Conflicts Can Be Resolved by Downshifting?
8.2.5 Contextually Triggered Downshifting
8.2.6 A Note on Downshifting Versus Ambiguity
8.3 How Mess Mass Counts
References
Chapter 9: The Structure of Classifier and Measures Phrases
9.1 Some Properties of Classifiers and Measures in English and Dutch
9.2 Classifier and Measure Structures
9.3 Rothstein´s Analysis
9.4 Landman´s Structures
9.5 The Case Against Rothstein´s Analysis of Measure Phrases
9.5.1 Three Salient Features Rothstein´s Analysis
9.5.2 What Is the Head of the Measure Phrase?
9.5.3 What Is the Constituent Structure of the Measure Phrase?
9.5.4 Do We Need NP[of] [plur] Reanalyzed as NP[of] [mass]?
9.6 A More General Perspective
References
Chapter 10: Iceberg Semantics for Classifier and Measure Phrases
10.1 Measure i-Sets and Classifier i-Sets
10.2 Why Measure Phrases Are Mess Mass
10.2.1 The Body of the Measure
10.2.2 Measure Functions
10.2.3 Measure i-Sets
10.2.4 The Base of the Measure i-Set
10.2.5 Measure Phrases Are Mess Mass
10.3 Classifier Semantics
10.3.1 Classifier i-Sets
10.3.2 Container Classifiers
10.3.3 The Function Contents
10.3.4 Portion Readings
10.3.5 Shape Classifiers
10.3.6 Contents Classifiers
10.4 Shifting Between Classifiers and Measures
10.4.1 Shifting Measures to Container Classifiers
10.4.2 Shifting Measures to Contents Classifiers
10.4.3 Shifting Classifiers via Measures to Container and Contents Classifiers
10.4.4 Shifting Measures to Portion Classifiers
10.4.5 Shifting Classifiers Via Measures to Portion Classifiers
10.5 Summary of the Measure and Classifier Readings
References
Chapter 11: Elaborations, Developments, Justifications
11.1 Measure Comparison of Neat Mass Nouns
11.1.1 Iceberg Semanics for Partitives
11.1.2 Conservative Semantics for Measure Comparison Most
11.1.3 Non-downshifted Measure Readings of Neat Mass Nouns
11.2 Luxury Icebergs and Singular Shift
11.3 Pragmagic
11.3.1 A Caveat About Implementing Pragmagic
11.3.2 Doppelgänger
11.3.3 Indexing
11.4 Abstract Mass Nouns
11.4.1 Neat Mass Uses of Abstract Mass Nouns
11.4.2 Crime as a Neat Mass Noun
11.4.3 Degree Mass Nouns
11.5 Apologia
References
Index