In this paper, we introduce for the first time a Distributional Model for computing semantic com- plexity, inspired by the general principles of the Memory, Unification and Control framework (Hagoort, 2013; Hagoort, 2016). We argue that sentence comprehension is an incremental pro- cess 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).
Towards a Distributional Model of Semantic Complexity
CHERSONI, EMMANUELEPrimo
;LENCI, ALESSANDROCo-primo
2016-01-01
Abstract
In this paper, we introduce for the first time a Distributional Model for computing semantic com- plexity, inspired by the general principles of the Memory, Unification and Control framework (Hagoort, 2013; Hagoort, 2016). We argue that sentence comprehension is an incremental pro- cess 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).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
