Going organic: Building an experimental bottom-up dictionary of verbs in science
Résumé
Choosing what headwords to enter in a dictionary has always been a major question in lexicographical practice. Corpora have greatly helped ease both the choice of words to add, and those to remove, by resorting to frequency counts so as to monitor usage over time. This has been particular valuable in the building of learners dictionaries as, however good earlier word lists may have been, they were built largely in intuition whereas, corpora allow the consultation of large reference corpora for a better picture of current realities. In specialised dictionaries dealing with terminological issues, pure frequency is not a feasible solution for headword extraction. However, linked with extraction patterns and statistical tools, corpora still play a major role in supplying information on terms in use. In this research we aim to tackle a situation that lies in between the needs of an advanced learners dictionary and those of a terminological dictionary in attempting to build a pattern dictionary for verbs used in scientific research papers. In order to select verbs for this dictionary and put them into classes, we propose to use collocational relationships as a tool for both selection and analysis of patterns. The principle here is that a series of high frequency verbs can provide the seeds from which prototypical patterns can be extracted. By moving backwards and forwards from verb to argument and back pattern are revealed that use the statistical selectionning to highlight verbs lower in the frequency list that would otherwise be overlooked. Thus patterns will naturally enlarge the word list by selecting what is statistically significant with a textual environment. These patterns not only illustrate typical usage in a specialised environment, but will also group verbs according to textual functions as authorial positioning and description of processes.
Origine : Accord explicite pour ce dépôt
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