Corpus-based research in pragmatics has been limited by the lack of adequate corpora. This is particularly true for languages other than English and for openly available data. However, the production of pragmatically annotated corpora could greatly facilitate research on the interaction of different language levels and enable their use in more applied areas such as language teaching, textbook production or the training of language professionals.
Pragmatic annotation poses many challenges, such as encoding the meaning of utterances that depend on extratextual context and are dominated by implicit language. Another bottleneck is the annotation criteria, which can be ambiguous, especially when considering socio-pragmatic aspects in an ecological setting. The ideal scenario is to have robust pragmatic annotation tools.
New strategies have been developed to overcome these obstacles with the Ladder and DisDir corpora. The data are restricted to experimental settings where extratextual variables are controlled by standardised Discourse Completion Tasks (DCT). Thanks to the selection of specific speech acts, the applied taxonomy allows the coding of utterances that bypass the detection of implicit meaning. The annotation is automatically enriched by a machine learning application, which will form the basis for semi-automatic annotation.
The final product will provide an online platform that allows linguists to search the aforementioned corpora for speech acts of requests and cancellations i in different languages and varieties.
