By Steven L. Small, Garrison W Cottrell, Michael K Tanenhaus
The most often used phrases in English are hugely ambiguous; for instance, Webster's 9th New Collegiate Dictionary lists ninety four meanings for the note "run" as a verb on my own. but humans not often become aware of this ambiguity. fixing this puzzle has commanded the efforts of cognitive scientists for a few years. the answer pretty much pointed out is "context": we use the context of utterance to figure out the correct meanings of phrases and sentences. the matter then turns into specifying the character of context and the way it interacts with the remainder of an realizing approach. the trouble turns into specifically obvious within the try to write a working laptop or computer software to appreciate typical language. Lexical ambiguity solution (LAR), then, is among the imperative difficulties in traditional language and computational semantics research.
A selection of the simplest study on LAR to be had, this quantity deals eighteen unique papers by way of prime scientists. half I, laptop versions, describes 9 makes an attempt to find the approaches useful for disambiguation via enforcing courses to do the activity. half II, Empirical experiences, is going into the laboratory surroundings to ascertain the character of the human disambiguation mechanism and the constitution of ambiguity itself.
A basic target of this quantity is to suggest a cognitive technology standpoint coming up out of the conjunction of labor and methods from neuropsychology, psycholinguistics, and synthetic intelligence--thereby encouraging a better cooperation and collaboration between those fields.
Lexical Ambiguity Resolution is a useful and available resource ebook for college students and cognitive scientists in AI, psycholinguistics, neuropsychology, or theoretical linguistics.
Read or Download Lexical Ambiguity Resolution. Perspective from Psycholinguistics, Neuropsychology and Artificial Intelligence PDF
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Additional resources for Lexical Ambiguity Resolution. Perspective from Psycholinguistics, Neuropsychology and Artificial Intelligence
Attempting to organize the expert networks in accordance with the observed relative frequencies of the different meanings of a word. 4); 3. Attempting to determine what parts of the word expert process are independent of each other, possibly across the entries as defined now. " I f such parts can be found, the nets could be reorganized in a more "semantic" way and a limited form of parallelism could be introduced; 4. Further refinement of the expert representation language through extended application of WEP to broader samples from natural languages; 5.
Butterworth, B. 1983b. Lexical representation. ), Language Production Volume 2. Development, Writing and Other Language Processes, pp. 257-294. London: Academic. S. et al. 1981. Effects of prior context upon the integration of lexical information during sentence processing. Journal of Verbal Learning and Verbal Behavior 20:445^153. Caplan, D. ). 1980. Biological Studies of Mental Processes. Cambridge: MIT Press. Carlson, G. K. Tanenhaus. 1984. Lexical meanings, structural meanings, and concepts.
1975. Proceedings of the First Annual Meeting of the Berkeley Linguistic Society, Berkeley, California. M. F. Loftus. 1975. A spreading-activation theory of semantic processing. Psychological Review 82(6):407-428. Connine, C. et al. 1984. Verb frame preferences: Descriptive norms. Journal of Psycholinguistic Research 13:307-319. Conrad, C. 1974. Context effects in sentence comprehension: A study of the subjective lexicon. Memory and Cognition 2(la):130-138. E. T. ). 1979. Sentence Processing: Psycholinguistic Studies Presented to Merrill Garrett.