One of the longest-running, and in many respects the least helpful, methodological debates in corpus linguistics concerns the spat between so-called corpus-driven and corpus-based linguists.
I say that this has been largely unhelpful because it has encouraged a dichotomy which is almost certainly false, and the focus on whether it is ‘right’ to work from corpus data upwards towards theory, or from theory downwards towards text, distracts from some serious methodological challenges we need to consider (see other posts on this blog).
Usually this discussion reviews the achievements of the most well-known corpus-based linguist, John Sinclair, in building the Collins Cobuild Corpus, and deriving the Collins Cobuild Dictionary (Sinclair et al. 1987) and Grammar (Sinclair et al. 1990) from it.
In this post I propose an alternative examination.
I want to suggest that the greatest success story for corpus-based research is the development of part-of-speech taggers (usually called a ‘POS-tagger’ or simply ‘tagger’) trained on corpus data.
These are industrial strength, reliable algorithms, that obtain good results with minimal assumptions about language.
So, who needs theory? Continue reading