A Description of Texts in a Corpus: 'Virtual' and 'Real' Corpora

The extensive use of computer-based corpora for a range of language studies has led to the proliferation of the ways in which texts within an individual corpus are organised Basically, the organisation reflects the immediate needs of a group of well motivated users, like lexicographers or terminologists. This means that the subsequent generation of corpus users are forced to use a classification of texts according to categories they may not be familiar with or may not be comfortable with or both. There is an urgent need to have a facility in corpus management system that allow its users to use their own classification system to categorise texts in a corpus. That is, the users should be able to choose, for example, their own style, register, field, time span, author attributes for generating word lists, concordances, contextual examples etc. A lexicography/terminology management system, System Quirk, is described that can support such a virtual organisation of texts within a corpus. Introduction There are open questions in corpus linguistics related to how texts should be selected and, perhaps, more importantly for what purpose. Some argue that lexicographers and linguists should choose the texts themselves with some advice from teachers of English (Sinclair and colleagues in Sinclair 1987), whilst the corpus linguistics pioneers used a random-selection approach (cf. Lancaster Oslo Bergen Corpus and the Brown Corpus). Still others have argued that there should be an equal mixture of deliberately selected text and randomly selected text (see, for instance, Summers 1991). We hope that the discussion of how text is organised and, indeed, how representative text is chosen, will motivate the reader to consider various parameters that can label a text. These parameters may include the medium in which the text is delivered books, magazines, journals, leaflets, letters; the genre of the text, fiction or non-fiction, whether it is imaginative or informative, persuasive or instructional. The register and the domain of the text are equally important parameters. Furthermore, there are some atomic features of a text including author’s age and sex, publication period, language variety and so on. (One might consider the use of ‘contextual correlates’ described by Halliday to categorise texts in terms of their tenor and field, given that the mode of the language in the text corpora is textual). The LOB corpus was categorised into informative texts and imaginative texts. The latter category contains mainly works of fiction, ranging from detective fiction to