Opposition theory and computational semiotics

  • Dan Assaf Independent researcher, Petach Tikva
  • Yochai Cohen Gilasio Coding Ltd., Tel-Aviv
  • Marcel Danesi University of Toronto, Toronto
  • Yair Neuman Department of Education, Ben-Gurion University of the Negev
Keywords: opposition theory, computational semiotics, metaphor identification


Opposition theory suggests that binary oppositions (e.g., high vs. low) underlie basic cognitive and linguistic processes. However, opposition theory has never been implemented in a computational cognitive-semiotics model. In this paper, we present a simple model of metaphor identification that relies on opposition theory. An algorithm instantiating the model has been tested on a data set of 100 phrases comprising adjective-noun pairs in which approximately a half represent metaphorical language-use (e.g., dark thoughts) and the rest literal language-use (e.g., dark hair). The algorithm achieved 89% accuracy in metaphor identification and illustrates the relevance of opposition theory for modelling metaphor processing.


Download data is not yet available.

Metrics (links, shares etc)

Metrics Loading ...