Feature overwriting as a finite mixture process: Evidence from comprehension data

Shravan Vasishth; Lena A. Jäger; Bruno Nicenboim

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arXiv · 1703.04081

Feature overwriting as a finite mixture process: Evidence from comprehension data

Shravan Vasishth·Lena A. Jäger·Bruno Nicenboim

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Abstract

The ungrammatical sentence "The key to the cabinets are on the table" is known to lead to an illusion of grammaticality. As discussed in the meta-analysis by Jaeger et al., 2017, faster reading times are observed at the verb are in the agreement-attraction sentence above compared to the equally ungrammatical sentence "The key to the cabinet are on the table". One explanation for this facilitation effect is the feature percolation account: the plural feature on cabinets percolates up to the head noun key, leading to the illusion. An alternative account is in terms of cue-based retrieval (Lewis & Vasishth, 2005), which assumes that the non-subject noun cabinets is misretrieved due to a partial feature-match when a dependency completion process at the auxiliary initiates a memory access for a subject with plural marking. We present evidence for yet another explanation for the observed facilitation. Because the second sentence has two nouns with identical number, it is possible that these are, in some proportion of trials, more difficult to keep distinct, leading to slower reading times at the verb in the first sentence above; this is the feature overwriting account of Nairne, 1990. We show that the feature overwriting proposal can be implemented as a finite mixture process. We reanalysed ten published data-sets, fitting hierarchical Bayesian mixture models to these data assuming a two-mixture distribution. We show that in nine out of the ten studies, a mixture distribution corresponding to feature overwriting furnishes a superior fit over both the feature percolation and the cue-based retrieval accounts.

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Shravan Vasishth, Lena A. Jäger, Bruno Nicenboim. 2017-03-12. Feature overwriting as a finite mixture process: Evidence from comprehension data. https://arxiv.org/abs/1703.04081

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