Y. Wilks (1978) Making preferences more active, Artificial Intelligence, 11.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....in lhe syntaclic dicliol aly. This kind of ambiguily can The Conceptual Graph model The Concoplual Graph model is a very promising unified model, because it generalizes many ideas contained in preceding works on natural language semantics, such as Fillmore [7] Schank [9] Montague [5] Wilks [12], and Karnp [8] for example. For the sake of clarity, we briefly recall here the Conceptual Graph model introduced by J.F. Sowa [10] A Conceptual Graph is an orienled graph made up of concept nodes related by conceptual relation edges. The concel)ls are represented by boxes. the. relations by ....

Y.A. Wilks, Making preferences more active, Artificial Intelligence, Vol 11, 3, 1978, pp 197-224. 244 6 '

....not provide entries for all idioms, and the entries it does provide do not always include a sense for the occurrences observed in the corpus. It is important to recognize idioms, because interpreting their constituent words separately would often change the meaning of the sentence (cf. e.g. Wilks 1977 and Wilensky Arens 1980) Our coding instructions specify that the tagger should attempt to identify idioms even if WordNet does not provide an entry for it. The preprocessor assists in this task, by identifying potential idioms. The following are strategies we found useful in dealing with the ....

Wilks, Y. 1977. Making preferences more active. Artificial Intelligence 8, pp. 75--97.

....provides the system with no basis for the prediction or classification of new uses as they are encountered. At the opposite end of the spectrum, lie approaches that are based on analogy or similarity (Carbonell, 1981; DeJong and Waltz, 1983; Fass, 1988; Gentner et al. 1988; Indurkhya, 1987; Wilks, 1978). These approaches assert that metaphors arise from an underlying conceptual similarity or analogy between the concepts representing the literal meaning of the words and the concepts underlying the ultimate meaning of the utterance. These approaches are at the opposite end of the spectrum because ....

Wilks, Y. (1978). Making preferences more active. Artificial Intelligence, 11:197--223.

....of metaphors in the language. This approach follows on the metaphor work of Lakoff and Johnson (Lakoff and Johnson, 1980) and builds directly on the knowledge based computational approaches to metaphor of Jacobs and Norvig (Jacobs, 1985; Norvig, 1987) Earlier work on metaphor by Wilks and Hobbs (Wilks, 1978; Hobbs, 1979) are the most relevant computational predecessors to this work. 2.1 MIDAS Since the remainder of this paper focuses on our MetaBank work, this section will first briefly illustrate how such a knowledge base has been used. This is not intended as an exhaustive list since the ....

Wilks, Y. (1978). Making preferences more active. Artificial Intelligence, 11.

.... 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 significant timing difference from equivalent literal language. These results has been primarily ....

Wilks, Y. (1978). Making preferences more active. Artificial Intelligence, 11.

....detect that the utterance is metaphorical, or, more precisely, decide that the utterance should be taken metaphorically. With several other authors we would suggest that in many cases metaphoricity is raised as a strong possibility because of the violation of selection restrictions (Fass, 1997; Wilks, 1978), for example the restriction that gobble expects an animal agent. This approach could include noticing that store rooms in his mind violates a restriction of a meaning of in , for instance a restriction that the two things are usually either both physical or both abstract. Similarly for ....

Wilks, Y. (1978). Making preferences more active. Artificial Intelligence, 10, pp.75--97.

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Y. Wilks (1978) Making preferences more active, Artificial Intelligence, 11.

....but also, for example, Fass whose work was a direct continuation of that quoted above. Indeed, in Wilks (1972) procedures were programmed (and run over a set of newspaper editorials) to accommodate the divergent usage to that of an established sense of another word in the same text, while in Wilks (1978) programmed procedures were specified to accommodate such usage by constructing completely new sense entries. A much more significant omission, one that bears directly on his main claim and is not merely an issue of historical correctness, is the lack of reference to work in New Mexico and ....

Wilks, Y. (1978) Making Preferences more Active. Artificial Intelligence, vol. 11.

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Wilks, Y. (1978) Making preferences more active, Artificial Intelligence, 11.

....whose work was a direct continuation of that quoted above. Indeed, in Wilks [18] procedures were programmed (and run over a set of newspaper editorials) to accommodate such divergent corpus usage of one word to that of an established sense of a different word in the same text, while in Wilks [19] programmed procedures were specified to accommodate such usage by constructing completely new sense entries for the word itself. A much more significant omission, one that bears directly on his main claim and is not merely an issue of historical correctness, is the lack of reference to work in ....

Y. Wilks. Making preferences more active. Artificial Intelligence, 11(3), December 1978.

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