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Computational Linguistics - How Important Is Semantics? Compared to What?

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Introduction

Computational Linguistics - How Important Is Semantics? Compared to What? Semantics has to do with meaning, the nature of which has been the subject of much philosophical debate: what is it exactly and how can it be represented? This essay is concerned with semantics from the perspective of Computational Linguistics, which is essentially concerned with building or attempting to build computational models of natural language. These Natural Language Processing or Understanding systems have a wide range of practical applications as well as providing insight into human understanding and perception. The prominance of semantics in the title can be taken as suggesting that it is indeed highly relevant to Computational Linguistics. However it is also implied, quite correctly, that semantics is not the only relevant area of interest. Natural Language systems usually have a number of different components and briefly outlining them here will help to put semantics in context. Phonetics is concerned with the analysis of spoken language. It is generally considered to be a specialized area of research and many centres for Computational Linguistics deal mainly with written language. Morphology involves the analysis of the composition and (and also meaning) of individual words. Often at this stage that syntactic categories are assigned to words, since interpretation of affixes may depend on the category of a word. For example, drinks could be either a plural noun or a first person singular verb. Syntactic analysis imposes structure on a flat string of words according to the grammatical categories of words. ...read more.

Middle

(5) My car drinks petrol If the verb drink is specified in the lexicon as requiring an animate subject the sentence will be rejected as nonsensical, when in fact it is not. Wilks (1975a) introduced the idea of preference semantics, whereby dispreferred readings can be allowed when the preferred readings are not present However, metaphors can be shown to be systematic and preference semantics does not exploit this fact. Semantic features are a rather crude technique for resolving ambiguity and have significant problems, such as determining the correct set of features in the first place and the need to introduce increasingly finer grained features. Furthermore, very new word may require a new feature to be added to the lexicon. As the number of features grows the lexicon becomes unwieldy. Some more elegant way of representing meaning or knowledge is required. Semantics and Knowledge are inextricably linked. The amount of knowledge needed to understand even a simple children's story is emense and the problems of knowledge representation are of central concern to Computational Linguistics and Artificial Intelligence. No uniform semantics representation language has emerged and consequently there are different competing classes of representation. Each has advantages and disadvantages and useful areas of application. First order logic and equivalent expressions have become very popular as a way to represent natural languge meanings. Logic oriented programming languages such as Prolog reflect or are a contributing cause of this and first-order logic can also be used by systems for database retrieval. ...read more.

Conclusion

There are different computational approaches to this problem. Heuristics based on recency are easy to implement, but a pronoun often refers to an item which is not in the previous sentence. This gives rise to the need for a more thoughtful analysis. Grosz maintains that discourse is tree shaped rather than linear and a reference may be back to an object which is chronolgically distant, but close in underlying discourse structure. This is strong argument for getting the theory behind the computational implementation correct. Nonlinguistic contexts provide knowledge about the person who produced the utterance, the goals of the communication and various other things which we use to understand utterances. (9) Did you see Bob? (i) The speaker wants to know if the addressee visually perceived Bob (ii) Bob was wearing purple flares. The speaker knows the addressee saw Bob. The speaker is commenting on this fact. The above sentence could have interpretation (i) or (ii) according to alternate contexts. In a complete system each stage has a part to play. Semantics broadens the applications of a system beyond those made possible by syntax alone, but a broader context than that considered by semantics needs to be taken into account for any serious understanding to take place. Semantics does have a central role to play in NLP systems, but the attendant problems of knowledge representation mean that this role is somewhat inhibited. A further point is that the nonlinear interaction between the different linguistic components of a system needs to be given more attention. The revised framework which would hopefully result from such research would provide a better context within which to re-examine the relative importance of semantics. ...read more.

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