Computational and empirical exploration of the interaction between semantics and pragmatics in vague language
Abstract/Contents
- Abstract
- Some language is straightforward to interpret, regardless of the context. Other language is more vague, and requires a context in order to reach a concrete interpretation. This work is focused on formal models of vagueness in language, which requires a joint inference about the person's intention (i.e. what information they're trying to convey) and the meanings of the words they are using in this context. In this work, we present several empirical and model explorations of how people use vague language. We provide experimental exploration of how the particular prior expectations and numeric amounts in sorites paradox lead to different endorsements of the premises. We show how a simple extension of an RSA scalar adjectives model quantitatively predicts endorsement levels for sorites premises. We further modify this adjective model to account for intensifying degree adverbs, and demonstrate a surprising prediction of this model: that the form and meaning of intensifying degree adverbs are closely related, with intensifier degree proportional to utterance cost (where cost can be approximated by length of phrase or in inverse frequency). Finally, we apply principles of pragmatic reasoning to the meanings of different periphrastic causal expressions and compare the predictions of two pragmatic models to participants forced choice responses. Much of language is inherently vague, and so in order to communicate, people must reason over uncertainty about the particular meanings of their words in context. This leads to surprising inferences and relationships between utterances under standard logical approaches to semantics, which can be explained by pragmatic principles of communication.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2020; ©2020 |
| Publication date | 2020; 2020 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Bennett, Erin Domenica |
|---|---|
| Degree supervisor | Gerstenberg, Tobias |
| Degree supervisor | Goodman, Noah (Noah D.) |
| Thesis advisor | Gerstenberg, Tobias |
| Thesis advisor | Goodman, Noah (Noah D.) |
| Thesis advisor | Frank, Michael |
| Degree committee member | Frank, Michael |
| Associated with | Stanford University, Department of Psychology |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Erin D. Bennett. |
|---|---|
| Note | Submitted to the Department of Psychology. |
| Thesis | Thesis Ph.D. Stanford University 2020. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2020 by Erin Domenica Bennett
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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