Metaphor: An Inescapable Phenomenon in Natural-Language Comprehension
Jaime G. Carbonell
A dream of many computational linguists is to produce a natural-language analyzer that tries its best to process language that "almost but not quite" corresponds to the system's grammar, dictionary, and semantic knowledge base. In addition, some of us envision a language analyzer that improves its performance with experience. To these ends, I developed the project and integrate algorithm, a method of inducing possible meanings of unknown words from context and storing the new information for eventual addition to the dictionary ( Carbonell, 1979). Although useful, this mechanism addresses only one aspect of the larger problem -- accuring certain classes of word definitions in the dictionary. In this chapter, I focus on the problem of augmenting the power of a semantic knowledge base used for language analysis by means of metaphorical mappings.
The pervasiveness of metaphor in every aspect of human communication has been convincingly demonstrated by Lakoff and Johnson ( 1980), Ortony ( 1980), Hobbs ( 1979), and many others. However, the creation of a process model to encompass metaphor comprehension has not been of central concern.1 From a computational standpoint, metaphor has been viewed as an obstacle, to be tolerated at best and ignored at worst. For instance, Wilks ( 1977) gives a few rules____________________