Abstract

Scalar focus operators like even, only, etc. interact with scales, i. e., ordered sets of alternatives that are referenced by focus structure. The scaling dimensions interacting with focus operators have been argued to be semantic (e. g. entailment relations, probability) in earlier work, but it has been shown that purely semantic analyses are too restrictive, and that the specific scale that a given operator interacts with is often pragmatic, in the sense of being a function of the context. If that is true, the question arises what exactly determines the (types of) scales interacting with focus operators. The present study addresses this question by investigating the distributional behaviour of the additive scalar particle even relative to scales whose focus alternatives are ordered in terms of evaluative attitudes (positive, negative). Our hypothesis is that such evaluative attitudinal scales are at least partially functions of the lexical material in the sentential environment. This hypothesis is tested by determining correlations between sentence-level attitudes and lexically encoded attitudes in the relevant sentences. We use data from the Europarl corpus, a corpus of scripted and highly elaborated political speech, which is rich in argumentative discourse and thus lends itself to the study of attitudes in context. Our results show that there are in fact significant correlations between (manual) sentence-level evaluations and lexical evaluations (determined through machine learning) in the textual environment of the relevant operators. We conclude with an outlook on possible extensions of the method applied in the present study by identifying attitudinal patterns beyond the sentence, showing that positively and negatively connotated instances of even differ in terms of their argumentative function, with positive even often marking the climax and endpoint of an argument, while negative even often occurs in qualifying insertions like concessive parentheses. While we regard our results as valid, some refinements and extensions of the method are pointed out as necessary steps towards the establishment of an empirical sentence semantics, in the domain of scalar additive operators as well as more generally speaking.

Highlights

  • 1 Introduction Scalar additive operators like Engl. even, only, Fr. même, seulement, Germ. sogar, nur, etc. are so called because they systematically interact with scales, i. e., sets of paradigmatic alternatives that are ordered in some way

  • We focus on the English additive scalar operator even, leaving scalar additive operators from other languages and restrictive operators like only for future research

  • We have focused on one type of scale and context feature, i. e., evaluative attitudes

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Summary

Introduction

Scalar additive operators like Engl. even, only, Fr. même, seulement, Germ. sogar, nur, etc. are so called because they systematically interact with scales, i. e., sets of paradigmatic alternatives that are ordered in some way. If the interpretation of even and comparable operators is context-dependent, the question arises what types of context features are responsible for determining the nature of the scales interacting with even This question can only be answered by carrying out empirical studies of relevant operators in their textual environments, and this is precisely what the present study intends to do. Our underlying hypothesis is that the lexical material in the co-text of an even-sentence has an influence on the type of scale that even interacts with. This hypothesis is operationalized as a hypothesis about correlations between lexically encoded connotations in the sentential environment of even, on the one hand, and proposition-level attitudes associated with even, on the other.

From semantic to pragmatic scales
Attitude scales interacting with even
Attitudes associated with even
The corpus and the sample
Manual annotation
Lexical connotations
Quantifying lexical connotations
Testing proposition-level and lexical annotations for correlations
An outlook
Findings
Conclusions

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