Systemic Functional Linguistics and Context
From Theory to Model and Application
Rebekah Wegener [+–]
University of Salzburg
Context is crucial for advances in artificial intelligence and AI researchers look for models that will help them to solve the challenges that they face in understanding emotion, building dialogic systems and other problems that fall under contextual AI. Some model of context will also be needed in many other fields which explore causation. Without a strong contribution from context, the description of semantic behaviour is not enough for the solution of real world problems to which we bring our linguistic models. While it has typically been conceded that context is fundamental to meaning, it had been, and in some quarters still is, considered too amorphous for scientific investigation. Indeed, unless the bounds of context are very carefully defined, there is certainly a risk that it becomes a description of everything (see for example Cook 1990). Within linguistics this concern has often been addressed by reducing the concept of context to the micro scale of the surrounding words or sounds (what we might call co-text). The obverse of this is the Ethnographic approaches, including Hymes (1962) and later Duranti (1992) and others, who have conceptualized context as the framework of arrangements that pertain to the understanding of the whole communicative event and indeed multiple events. The formalization of a level of context as part of a poly-systemic representation of language has long been emphasized in the work of systemic functional linguists, especially Halliday and Hasan (e.g. 1985). Their approach can be traced back to J.R. Firth’s early collaborations with the anthropologist Malinowski (Butt and Wegener, 2008 but also Butt, 2001). These linguists have worked to systematize the concept, and provide a comprehensive account of the relations of context and text (Hasan, 1999).
This monograph provides a background to the role of context within SFL historically and at a theoretical level before looking at how we model context for different applications. It concludes by considering how SFL approaches to context relate to other functional models as well as looking at some of the challenges and future directions for research on context.
Table of Contents
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