A. Zarcone and J. Utt and S. Pado. Modeling covert event retrieval in logical metonymy: probabilistic and distributional accounts. To appear in Proceedings of CMCL 2012. Montreal, Canada.
Logical metonymies (The student finished the beer) represent a challenge to compositionality since they involve semantic content not overtly realized in the sentence (covert events -> drinking the beer). We present a contrastive study of two classes of computational models for logical metonymy in German, namely a probabilistic model and a distributional, similarity-based model. We build both models from the SDEWAC corpus and evaluate them against a dataset from a self-paced reading and a probe recognition study for their sensitivity to thematic fit effects via their accuracy in predicting the correct covert event in a metonymical context. The similarity-based models allow for better coverage while maintaining the accuracy of the probabilistic models.
@InProceedings{zarcone12:modeling,
author = {Alessandra Zarcone and Jason Utt and Sebastian Pad\'o},
title = {Modeling covert event retrieval in logical metonymy:
Probabilistic and distributional accounts},
booktitle = {Proceedings of the Workshop on Cognitive Modeling and
Computational Linguistics},
year = 2012,
address = {Montreal, Canada}}