Abstract
Discourse connectives are procedural markers of textual cohesion that have long been an object of study in the Geneva school of pragmatics. In this chapter, we argue that Jacques Moeschler’s descriptions of causal connectives have contributed to provide theoretical insights on the nature of their procedural meaning, which have been recently shown to be compatible with models of human cognition from processing and acquisition studies across several languages. We review these studies in Sects. 2 and 3 respectively. In many of his contributions, Jacques Moeschler has also strived to find precise and testable features of connectives, with a potential for empirical validations in computer applications. In Sect. 4, we describe recent attempts to label automatically some of the meanings of connectives, using parallel corpora as training data, and show that this procedure improves their translation by automatic systems.
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Notes
- 1.
Of course, as discussed by Zufferey et al. (2012, Sect. 2.2), the discourse relation actually signaled in context could also be the result of a hearer’s (or annotator’s) inferences, and should not always be considered as part of the core semantic meaning of a connective. Annotation guidelines should state specific instructions on this point, and frequency studies should consider the possibility of discarding infrequent pragmatic meanings from the core set of meanings associated to a connective.
- 2.
COMTIS: Improving the Coherence of Machine Translation Output by Modeling Intersentential Relations was a project involving the University of Geneva (and in particular Jacques Moeschler and his team) and the Idiap Research Institute, supported by the Swiss National Science Foundation under its Sinergia program (2010–2013), see http://www.idiap.ch/project/comtis.
- 3.
This is the goal of the MODERN Sinergia project (Modeling Discourse Entities and Relations for Coherent Machine Translation) involving the University of Geneva (Jacques Moeschler’s team), the Idiap Research Institute, and the Universities of Zurich and Utrecht. MODERN is supported by the Swiss National Science Foundation under its Sinergia program (2013–2017), see http://www.idiap.ch/project/modern.
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Zufferey, S., Popescu-Belis, A. (2017). Discourse Connectives: Theoretical Models and Empirical Validations in Humans and Computers. In: Blochowiak, J., Grisot, C., Durrleman, S., Laenzlinger, C. (eds) Formal Models in the Study of Language. Springer, Cham. https://doi.org/10.1007/978-3-319-48832-5_20
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