Towards a Distributional Model of Semantic Complexity

Domain:

natural language processing

Record type:

paper

Creator:

CheBlaLen

Editor:

LabUniANR

Publisher:

CCSD

Host:

International audience In this paper, we introduce for the first time a Distributional Model for computing semantic complexity , inspired by the general principles of the Memory, Unification and Control framework (Hagoort, 2013; Hagoort, 2016). We argue that sentence comprehension is an incremental process driven by the goal of constructing a coherent representation of the event represented by the sentence. The composition cost of a sentence depends on the semantic coherence of the event being constructed and on the activation degree of the linguistic constructions. We also report the results of a first evaluation of the model on the Bicknell dataset (Bicknell et al., 2010).

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