Natural Language Concept Analysis

I i I / I / l I l I / / I Natural Language Concept Analysis Vera Kamphuis Dept. of Language and Speech University of Nijmegen The Netherlands v. kamphuis@let, kun. nl Janos Sarbo ~ Computing Science Institute University of Nijmegen The Netherlands j anos@cs, ktm. nl Abstract Can we do text analysis without phrase struc- ture? We think the answer could be positive. In this paper we outline the basics of an under- lying theory which yields hierarchical structure as the result of more abstract principles relat- ing to the combinatorial properties of linguistic units. We discuss the nature of these proper- ties and illustrate our model with examples. Keywords Language processing, relational model. 1 Introduction In most mainstream approaches to natural language modelling and parsing, some form of hierarchical structure plays a central role. The most obvious case in point is phrase structure. However, while the latter notion has shown its theoretical relevance in many ways, practical applications based on phrase structure description are not without problems. The main reason for this is the high flexibility of natural language. In performance data (i.e. actual language use), many disruptions of, and variations on stan- dard phrase structure patterns occur. As a result, application of phrase structure-based parsers in nat- ural language processing shows only limited success. This has inspired a search for alternative methods, such as statistical based or lexicon-driven parsing. In our search for a solution to the problems men- tioned we decided to take one step back, and exam- ine the underlying nature of hierarchical structure in general, and phrase structure in particular. Our aim in doing so was to find a more principled solution to the problems of linguistic analysis and parsing. We looked for ways to derive structural information from input, and to incorporate this in a mathemat- ically well-founded theory of knowledge representa- tion. As a result we found a level of abstractness that, in principle, allows language-independent mod- elling and analysis. In our approach we capitalise on the property that the information carriers, the lexical items, are 'will- ing' to combine. These combinatorial properties are determined by inherent characteristics of lexi- ca/ items. Hierarchical structure follows naturally from the interaction of these properties, while leav- ing room for variation and flexibility in structural patterning. In our model of natural language (NL) the input is represented as a binary relation. This is due to the dichotomy of language, meaning that a classifica- tion of lexical items as objects and attributes can be made (we use the term "dichotomy" in a restricted sense: a division into two mutually exclusive parts). The two classes are interrelated, and their relation can be dete ~rrnined merely on the basis of lexicai in- formation and some general principles, like word or- der (e.g. SVO). The relation between the classes is due to the principle of relatedness. This princi- ple entails that any non-empty set of objects implies the existence of a non-empty set of attributes (prop- erties) it …

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