Negation Generates Nonliteral Interpretations by Default

Rachel Giora, Elad Livnat, Ofer Fein, Anat Barnea, Rakefet Zeiman, Iddo Berger

Research output: Contribution to journalArticlepeer-review


Four experiments and 2 corpus-based studies demonstrate that negation is a determinant factor affecting novel nonliteral utterance-interpretation by default. For a nonliteral utterance-interpretation to be favored by default, utterances should be potentially ambiguous between literal and nonliteral interpretations. They should therefore be (a) unfamiliar, (b) free of semantic anomaly or any kind of internal incongruity, and (c) unbiased by contextual information. Experiments 1-3 demonstrate that negative utterances, meeting these 3 conditions, were interpreted metaphorically (This is not a safe) or sarcastically (Ambitious she is not) when presented in isolation and were therefore processed faster in contexts strongly biasing them toward their nonliteral than toward their (equally biased) literal interpretation. Experiment 4 reduces the possibility that it is structural markedness on its own that induces nonliteralness. Two corpus-based studies provide corroborating evidence, supporting the view of negation as an operator generating nonliteral interpretations by default.

Original languageEnglish
Pages (from-to)89-115
Number of pages27
JournalMetaphor and Symbol
Issue number2
StatePublished - 1 Apr 2013
Externally publishedYes

Bibliographical note

Funding Information:
This research was supported by grants to the first author by the Israel Science Foundation (grant no. 436/12) and the Vice President for Research and Development at Tel Aviv University Encouragement Fund. We are also very grateful to members of our laboratory, Ari Drucker, Shir Givoni, and Itamar Mendelson who have been both highly critical and very supportive and to Mira Ariel, Ruth Filik, Ray Gibbs, and to an anonymous reviewer for very insightful comments, suggestions, and discussions. We are also deeply indebted to Ran Abramson and Amnon Lotan for programming and running the experiments.


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