this paper, I will discuss four major topics relating to current research in lexical semantics: methodology, descriptive coverage, adequacy of the representation, and the computational usefulness of representations. In addressing these issues, I will discuss what I think are some of the central problems facing the lexical semantics community, and suggest ways of best approaching these issues. Then, I will provide a method for the decomposition of lexical categories and outline a theory of lexical semantics embodying a notion of cocompositionality and type coercion, as well as several levels of semantic description, where the semantic load is spread more evenly throughout the lexicon. I argue that lexical decomposition is possible if it is performed generatively. Rather than assuming a fixed set of primitives, I will assume a fixed number of generative devices that can be seen as constructing semantic expressions. I develop a theory of Qualia Structure, a representation language for lexical items, which renders much lexical ambiguity in the lexicon unnecessary, while still explaining the systematic polysemy that words carry. Finally, I discuss how individual lexical structures can be integrated into the larger lexical knowledge base through a theory of lexical inheritance. This provides us with the necessary principles of global organization for the lexicon, enabling us to fully integrate our natural language lexicon into a conceptual whole

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The automatic disambiguation of word senses has been an interest and concern since the earliest days of computer treatment of language in the 1950's. Sense disambiguation is an “intermediate task ” (Wilks and Stevenson, 1996) which is not an end in itself, but rather is necessary at one level or another to accomplish most natural language processing tasks. It is

The resolution of lexical ambiguity is important for most natural language processing tasks, and a range of computational techniques have been proposed for its solution. None of these has yet proven effective on a large scale. In this paper, we describe a method for lexical disambiguation of text using the definitions in a machine-readable dictionm~j together with the technique of simulated annealing. The method operates on complete sentences and attempts to select the optimal combinations of word senses for all the words in the sentence simultaneously. The words in the sentences may be any of the 28,000 headwords in Longman's Dictionary of Contemporary English (LDOCE) and are disambiguated relative to the senses given in LDOCE. Our initial results on a sample set of 50 sentences are comparable to those of other researchers, and the fully automatic method requires no hand-coding of lexical entries, or hand-tagging of text. L

Word sense disambiguation (WSD) is a computational linguistics task likely to benefit from the tradition of combining different knowledge sources in artificial in telligence research. An important step in the exploration of this hypothesis is to determine which linguistic knowledge sources are most useful and whether their combination leads to improved results. We present a sense tagger which uses several knowledge sources. Tested accuracy exceeds 94 % on our evaluation corpus. Our system attempts to disambiguate all content words in running text rather than limiting itself to treating a restricted vocabulary of words. It is argued that this approach is more likely to assist the creation of practical systems. 1.

In this paper we investigate how discourse structure affects the meanings of words, and how the meanings of words affect discourse structure. We integrate three ingredients: a theory of discourse structure called sdrt, which represents discourse in terms of rhetorical relations that glue together the propositions introduced by the text segments; an accompanying theory of discourse attachment called dice, which computes which rhetorical relations hold between the constituents, on the basis of the reader's background information; and a formal language for specifying the lexical knowledge---both syntactic and semantic---called the lkb. Through this integration, we can model the information flow from words to discourse, and discourse to words. From words to discourse, we show how the lkb permits the rules for computing rhetorical relations in dice to be generalised and simplified, so that a single law applies to several semantically related lexical items. From discourse to words, we encode...

In this paper we describe the SSI algorithm, a structural pattern matching algorithm for WSD. The algorithm has been applied to the gloss disambiguation task of Senseval-3. 1

We have for several years been working on an approach to knowledge system building that argues for the existence of a close connection between the tasks which the knowledge system is intended to solve, the methods chosen for them and the vocabulary in which knowledge is to be modeled and represented. We trace the historical origins of the idea that we have called Generic Tasks, and outline their evolution and accomplishments based on them. We then critique their original implementations from the perspective of flexible integration. We follow this with an outline of our current generalization of the view in the form of a theory of task structures. We describe the architectural implications of this view and outline some research directions.

this paper, contains literal, metonymic, metaphorical, and anomalous semantic relations. The assertion-based class of relations are described in greater length in Fass (1989a)

Abstract not found