Abstract

This article considers the major change that has taken place in natural language processing research over the last five years. It begins by providing a brief guide to the structure of the field and then presents a caricature of two competing paradigms of 1980s NLP research and indicates the reasons why many of those involved have now seen fit to abandon them in their pure forms. Attention is then directed to the lexicon, a component of NLP systems which started out as Cinderella but which has finally arrived at the ball. This brings us to an account of what has been going on in the field most recently, namely a merging of the two 1980s paradigms in a way that is generating a host of interesting new research questions. The chapter concludes by trying to identify some of the key conceptual, empirical and formal issues that now stand in need of resolution.

Introduction

The academic discipline that studies computer processing of natural languages is known as natural language processing (NLP) or computational linguistics (the terms are interchangeable). NLP is most conveniently seen as a branch of AI, although it is a branch into which many linguists (and a few psycholinguists) have moved. In Europe, NLP is dominated by ex-linguists but this is not the case in the USA where there is a tradition of people moving into the field from a standard computer science background.

It is tempting to say that NLP is the academic discipline that studies computer processing of the written forms of natural languages. But that would be misleading. The discipline that studies computer processing of the spoken forms of natural languages is known as speech processin or just speech.

Introduction

In the section of Lyons' Semantics that deals with the distinction between homonymy and polysemy, he notes that a major criterion ‘is unrelatedness vs. relatedness of meaning … indeed, it is arguable that it is the only synchronically relevant consideration’ (1977: 551). However, he goes on to argue that all attempts ‘to explicate the notion of relatedness of meaning in terms of a componential analysis of the senses of lexemes … have so far failed’ (1977: 552–3). Although Lyons is sympathetic to a treatment of the lexicon that seeks to maximise polysemy at the expense of homonymy, he does not himself go on in that book to reconstruct the notion of relatedness of meaning that such a treatment requires.

Discussing polysemy some nine years earlier, Lyons was a little more explicit about what might be required: ‘Various … types of “extension” or “transference” of meaning were recognized by the Greek grammarians, and have passed into traditional works on rhetoric, logic, and semantics. Meanings that are more or less closely “related” in accordance with such principles are not traditionally regarded as being sufficiently different to justify the recognition of distinct words’ (1968: 406). Metaphorical extension is the only kind of extension explicitly discussed in connection with polysemy in Introduction to Theoretical Linguistics although it is clear from the quotation just given that it was not the only one that Lyons had in mind.

Abstract

We characterise a notion of prioritised multiple inheritance (PMI) and contrast it with the more familiar orthogonal multiple inheritance (OMI). DATR is a knowledge representation language that was designed to facilitate OMI analyses of natural language lexicons: it contains no special purpose facility for PMI and this has led some researchers to conclude that PMI analyses are beyond the expressive capacity of DATR. Here, we present three different techniques for implementing PMI entirely within DATR's existing syntactic and semantic resources. In presenting them, we draw attention to their respective advantages and disadvantages.

Introduction

‘Multiple inheritance’, in inheritance network terminology, describes any situation where a node in an inheritance network inherits information from more than one other node in the network. Wherever this phenomenon occurs there is the potential for conflicting inheritance, i.e. when the information inherited from one node is inconsistent with that inherited from another. Because of this, the handling of multiple inheritance is an issue which is central to the design of any formalism for representing inheritance networks. For the formalism to be sound, it must provide a way of avoiding or resolving any conflict which might arise. This might be by banning multiple inheritance altogether, restricting it so that conflicts are avoided, providing some mechanism for conflict resolution as part of the formalism itself, or providing the user of the formalism with the means to specify how the conflict should be resolved.