From truth conditions to processes: how to model the processing difficulty of quantified sentences based on semantic theory

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Dokumentart: PhDThesis
Date: 2017-08-03
Language: English
Faculty: 5 Philosophische Fakultät
Department: Allgemeine u. vergleichende Sprachwissenschaft
Advisor: Hamm, Fritz (Prof. Dr.)
Day of Oral Examination: 2017-07-14
DDC Classifikation: 400 - Language and Linguistics
Keywords: Linguistik , Psycholinguistik , Semantik , Quantor
Other Keywords:
Semantic Processing
Sentence-Picture Verification
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The present dissertation is concerned with the processing difficulty of quantified sentences and how it can be modeled based on semantic theory. Processing difficulty of quantified sentences is assessed using psycholinguistic methods such as systematically collecting truth-value judgments or recording eye movements during reading. Predictions are derived from semantic theory via parsimonious processing assumptions, taking into account automata theory, signal detection theory and computational complexity. Chapter 1 provides introductory discussion and overview. Chapter 2 introduces basic theoretical concepts that are used throughout the rest of the dissertation. In chapter 3, processing difficulty is approached on an abstract level. The difficulty of the truth evaluation of reciprocal sentences with generalized quantifiers as antecedents is classified using computational complexity theory. This is independent of the actual algorithms or procedures that are used to evaluate the sentences. One production and one sentence picture verification experiment are reported which tested whether cognitive capacities are limited to those functions that are computationally tractable. The results indicate that intractable interpretations occur in language comprehension but also that their verification rapidly exceeds cognitive capacities in case the verification problem cannot be solved using simple heuristics. Chapter 4 discusses two common approaches to model the canonical verification procedures associated with quantificational sentences. The first is based on the semantic automata model which conceives of quantifiers as decision problems and characterizes the computational resources that are needed to solve them. The second approach is based on the interface transparency thesis, which stipulates a transparent interface between semantic representations and the realization of verification procedures in the general cognitive architecture. Both approaches are evaluated against experimental data. Chapter 5 focuses on a test case that is challenging for both of these approaches. In particular, increased processing difficulty of `more than n‘ as compared to `fewer than n‘ is investigated. A processing model is proposed which integrates insights from formal semantics with models from cognitive psychology. This model can be seen as implementation and extension of the interface transparency thesis. The truth evaluation process is conceived of as a stochastic process as described in sequential sampling models of decision making. The increased difficulty of `fewer than n’ as compared to `more than n’ is attributed to an extra processing step of scale-reversal that precedes the actual decision process. Predictions of the integrated processing model are tested and confirmed in two sentence-picture verification experiments. Chapter 6 discusses whether and how the integrated processing model can be extended to other quantifiers. An extension to proportional comparative quantifiers, like `fewer than half’ and `more than half’ is proposed and discussed in the light of existing experimental data. Moreover, it is shown that what are called empty-set effects can be naturally derived from the model. Chapter 7 presents data from two eye tracking experiments that show that `fewer than’ leads to increased difficulty as compared to `more than’ already during reading. Moreover, this effect is magnified if such quantifiers are combined with overt negation. Potential accounts of these findings are discussed. Conclusions are summarized in chapter 8.

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