Encoding and Acquiring Meanings for Figurative Phrases
35936Authors
nan
Abstract
1.1 The Task Domain Here we address the problem of mapping phrase meanings into their conceptual representations. Figurative phrases are pervasive in human communication, yet they are difficult to explain theoretically. In fact, the ability to handle idiosyncrat- ic behavior of phrases should be a criterion for any theory of lexical representation. Due to the huge number of such phrases in the English language, phrase representation must be amenable to parsing, generation, and also to learning. In this paper we demonstrate a semantic representation which facili- tates, for a wide variety of phrases, both learning and parsing. 1.
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Encodinl~ and Acquiring Meanings for-Figurative Phrases * Michael G. Dyer Uri Zernik Artificial Intelligence Laboratory Computer Science Department 3531 Boelter Hall University of California Los Angeles, California 90024 Abstract 1.1 The Task Domain Here we address the problem of mapping phrase meanings into their conceptual representations. Figurative phrases are pervasive in human communication, yet they are difficult to explain theoretically. In fact, the ability to handle idiosyncrat- ic behavior of phrases should be a criterion for any theory of lexical representation. Due to the huge number of such phrases in the English language, phrase representation must be amenable to parsing, generation, and also to learning. In this paper we demonstrate a semantic representation which facili- tates, for a wide variety of phrases, both learning and parsing. 1. Introduction The phrasal approach to language processing [Backer75, Pawley83, Fillmore86] emphasizes the role of the lexicon as a knowledge source. Rather than maintaining a single generic lexical entry for each word, e.g.: take, the lexicon contains many phrases, e.g.: take over, take it or leave it, take it up with, take it for granted, etc. Although this approach proves effective in parsing and in generation [Wilensky84], there are three problems which require further investigation. First, phrase interaction: the lexicon provides representation for single phrases, such as take to task and make up one' s mind. Yet it is required to analyze complex clauses such as he made up his mind to take her to task. The problem lies with the way the meanings of the two phrases interact to form the compound meaning. Second, phrase ambiguity: [Zernik86] phrasal parsing shifts the task from single-word selection to the selection of entire lexical phrases. When a set of lexical phrases appear syntactically equivalent, i.e.: he ran into a friend, he ran into an 1986 Mercedes, he ran into the store, and he ran into trouble again, disambiguation must be performed by semantic means. The conditions which facilitate phrase discrimination reside within each lexical entry itself. Third, phrase idiosyncracy: the meaning representation of phrases such as: lay down the law VS. put one' s foot down, must distinguish the special use of each phrase. This paper is concerned in the representation of phrase meanings and the process of acquiring these meanings from examples in context. * This research was supported in part by a grant from the ITA Foundation. Consider the figurative phrases in the sentences below, as they are parsed by the program RINA [Zernik85a]. Sh The Democrats in the house carried the water for Reagan's tax-reform bill.** $2: The famous mobster evaded prosecution for years. Finally, they threw the book at him for tax evasion. Depending on the contents of the given lexicon, the program may interpret these sentences in one of two ways. On the one hand, assuming that the meaning of a phrase exists in the lexi- con, the program applies that meaning in the comprehension of the sentence. In S1, the program understands that the Demo- cratic representatives did the "dirty" …
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1.1 The Task Domain Here we address the problem of mapping phrase meanings into their conceptual representations. Figurative phrases are pervasive in human communication, yet they are difficult to explain theoretically. In fact, the ability to handle idiosyncrat- ic behavior of phrases should be a criterion for any theory of lexical representation. Due to the huge number of such phrases in the English language, phrase representation must be amenable to parsing, generation, and also to learning. In this paper we demonstrate a semantic representation which facili- tates, for a wide variety of phrases, both learning and parsing. 1.
Publication Details
- Paper ID:
- 35936
- Year:
- 1986
- Publication:
- TIPSTER
- Publication Type:
- conf
- DOI:
- nan