This book investigates the phenomenon of actuality inferences, in which claims of ability are interpreted as descriptions of actual events, instead of as descriptions of potentiality or possibility. The findings contribute to a growing body of research in which computational models serve as an analytic tool for lexical and compositional semantics.
This book investigates the phenomenon of actuality inferences, in which claims of ability are interpreted as descriptions of actual events, instead of as descriptions of potentiality or possibility. The findings contribute to a growing body of research in which computational models serve as an analytic tool for lexical and compositional semantics.
Prerna Nadathur is Assistant Professor in the Department of Linguistics at The Ohio State University. Her research examines connections between lexical meaning and sentence-level patterns of semantic and pragmatic interpretation, with a focus on formal approaches to the representation of causal meaning across the lexical and compositional levels. She received her PhD in Linguistics from Stanford University in 2019, and has since held positions at Heinrich Heine University in Düsseldorf, Berkeley, and the University of Konstanz.
Inhaltsangabe
1: Introduction 2: Setting the stage 3: Causal dependence in implicativity 4: Variable implicativity 5: Enough and too semantics 6: Aspect and actuality inferences 7: Ability, actuality, and implicativity 8: Conclusion Appendix A: Notes on causal necessity Appendix B: Sources for examples References Index
1: Introduction 2: Setting the stage 3: Causal dependence in implicativity 4: Variable implicativity 5: Enough and too semantics 6: Aspect and actuality inferences 7: Ability, actuality, and implicativity 8: Conclusion Appendix A: Notes on causal necessity Appendix B: Sources for examples References Index
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