Abstract
We present a computational model that provides a unified account of inference, coherence, and disambiguation. It simulates how the build-up of coherence in text leads to the knowledge-based resolution of referential ambiguity. Possible interpretations of an ambiguity are represented bycenters of gravity in a high-dimensional space. The unresolved ambiguity forms a vector in the same space. This vector is attracted by the centers of gravity, while also being affected by context information and world knowledge. When the vector reaches one of the centers of gravity, the ambiguity is resolved to the corresponding interpretation. The model accounts for reading time and error rate data from experiments on ambiguous pronoun resolution and explains the effects of context informativeness, anaphor type, and processing depth. It shows how implicit causality can have an early effect during reading. A novel prediction is that ambiguities can remain unresolved if there is insufficient disambiguating in formation.
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The research presented here was supported by Grants 575-21-007 and 451-04-043 of the Netherlands Organization for Scientific Research (NWO).
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Frank, S.L., Koppen, M., Noordman, L.G.M. et al. Coherence-driven resolution of referential ambiguity: A computational model. Memory & Cognition 35, 1307–1322 (2007). https://doi.org/10.3758/BF03193603
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DOI: https://doi.org/10.3758/BF03193603