James H. Martin. 1992. Computer understanding of conventional metaphoric language. Cognitive Science 16, 2 (1992), 233-270.  Home/Search   Document Details and Download   Summary   Related Articles   Check

.... are being modelled [Gerrig 1989b] The attempts to model computationally the metaphor understanding can be split in three classes: the knowledge intensive approaches, which make use of separate lexicon entries for words in the conventional metaphors ( Hirst 1987, Wilenky et al. 1980] cf. [Martin 1992]) the analogy based approaches [Carbonell 1982, Gentner et al. 1988, Indurkhya 1987] which try to use analogy mappings to comprehend metaphors, and the mixed approaches which make use of knowledge of conventional metaphors and try to extend this knowledge to novel metaphors [Martin 1992] We ....

.... cf. Martin 1992] the analogy based approaches [Carbonell 1982, Gentner et al. 1988, Indurkhya 1987] which try to use analogy mappings to comprehend metaphors, and the mixed approaches which make use of knowledge of conventional metaphors and try to extend this knowledge to novel metaphors [Martin 1992]. We shall overview some of the analogy based methods and a mixed approach due to Martin. 7.1 Analogy Based Models Carbonell proposes a model of metaphor understanding starting from Lakoff s idea of a basic system of conceptual metaphors. He assumes a set of such metaphors exist in the memory of ....

[Article contains additional citation context not shown here]

Martin J., 1992. Computer Understanding of Conventional Metaphoric Language. Cognitive Science, 16, pg. 233-270.

....to literal meaning as we have shown. Similar criticism applies to Tourangeau Sternberg (1982) Fauconnier (1984) Kittay (1987) Turner (1988) Nunberg (1995) and many others. The same shadowy definitions of figurative language are then often adopted by computational linguists (Fass, 1991; Martin, 1992). This leads to the fact that it is mostly not clear at all, which phenomena are treated by these approaches. In addition, a tendency can be observed in more formal approaches pressed by the need to look for computationally feasible definitions of metaphor or metonymy to consider ....

....is entirely based on syntactic relations that guide conceptual interpretation. In particular, and unlike most algorithmic accounts (Norvig, 1989; Fass, 1991; Pustejovsky, 1991; Hobbs et al. 1993) it does not rely at all upon the violation of selectional restrictions (for a notable exception, cf. Martin (1992)) since this criterion accounts only for a subset of the phenomena naturally recognized as figurative language. In addition, the syntax based proposal we make avoids to consider reference changes as an indicator of figurativeness as is commonly assumed (e.g. by Lakoff Johnson (1980) Instead, ....

Martin, J. (1992). Computer understanding of conventional metaphoric language. Cognitive Science, 16:233--270.

....in metonymy in general and the examples Lako and Johnson put forward suggest that it is this conventional kind of metonymy they are talking about. The same shadowy de nitions of gurative language are then often adopted by theoretical linguists [29, 17, 30, 23] as well as computational linguists [5, 21]. This leads to the fact that it is mostly not clear at all, which phenomena are treated by these approaches and how they discriminate di erent varieties of gurative speech from others. In addition, a tendency can be observed in more formal approaches pressed by the need to nd computationally ....

....of gurative speech. The criterion we formulate is based on syntactic relations only that guide conceptual interpretation. In particular, and unlike most algorithmic accounts [22, 5, 12, 24] it does not rely at all upon the violation of selectional restrictions (for a notable exception, cf. [21]) since this criterion accounts only for a subset of the phenomena naturally recognized as gurative language. In addition, the syntax based proposal we make avoids to consider reference changes as an indicator of gurativeness as is commonly assumed [19] It is inspired by Fauconnier s [6] ....

James Martin. Computer understanding of conventional metaphoric language. Cognitive Science, 16:233-270, 1992.

....noun phrases not marked by a sortal conflict will be in the focus of our future work. Possibly these data will provide further evidence for our claim that LMF approaches are infeasible to adequately account for metonymy interpretation. 14 There is one computational approach to metaphoric speech (Martin, 1992), however, which explicitly rejects the LMF model. Acknowledgements. K. Markert is a member of the Graduate Program on Human and Machine Intelligence at Freiburg University, which is funded by DFG. We thank our colleagues, in particular Susanne Schacht and Michael Strube, who commented on earlier ....

Martin, J. (1992). Computer understanding of conventional metaphoric language. Cognitive Science, 16:233--270.

....Approaches There exist a number of knowledge intensive methods for the acquisition of syntactic and semantic lexical knowledge. These systems rely heavily on either hand coded background knowledge (e.g. Berwick [1983] Granger [1977] Hastings et al. 1991] Lytinen and Roberts [1989] Martin [1992], Selfridge [1986] or detailed hand coded heuristics that describe how and when to acquire new word definitions (e.g. Jacobs and Zernik [1988] Wilensky [1991] Unfortunately, generating either world knowledge or acquisition heuristics is more difficult and time consuming than generating the ....

Martin, J. Computer Understanding of Conventional Metaphoric Language. Cognitive Science, 16(2):233--270, 1992.

....The correct and efficient application of this metaphoric knowledge to the interpretation of metaphoric language. Learning: The dynamic acquisition of new knowledge about metaphors for which no known metaphor provides a coherent explanation. Earlier descriptions of midas (Martin, 1990; Martin, 1992) give more complete details on these topics. 2.2 Knowledge Representation Consider the following simple example of a conventional unix metaphor. The metaphorical use of the word in reflects a systematic metaphorical structuring of Unix processes as enclosures. 6) I am in Emacs. Metaphors like ....

Martin, J. H. (1992). Computer understanding of conventional metaphoric language. Cognitive Science, 16(2):233--270.

.... 1984; Gildea and Glucksberg, 1983; Glucksberg et al. 1982; Kemper, 1989; Inhoff et al. 1984; Keysar, 1989; Ortony et al. 1978) These results have been used to both bolster and refute a bewildering array of mechanistic accounts of metaphor processing (Fass, 1991; Fass, 1988; Martin, 1990; Martin, 1992; Martin, 1994; Gentner et al. 1988; Gildea and Glucksberg, 1983; Russell, 1976; Wilks, 1978; Carbonell, 1981; Hobbs, 1979; Indurkhya, 1987) Perhaps the most well known result from this research is that appropriate contexts facilitate the processing of metaphor to the extent that there is no ....

Martin, J. H. (1992). Computer understanding of conventional metaphoric language. Cognitive Science, 16(2):233--270.

No context found.

James H. Martin. 1992. Computer understanding of conventional metaphoric language. Cognitive Science 16, 2 (1992), 233-270.

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC