Prediction in human parsing: towads a briad-coverage, cross linguistic model

Project Details

Key findings

(1) We formalized the notion of prediction in human parsing by developing a probabilistic framework for prediction-based parsing, consisting of a generation component and a verification component.
(2) We designed and implement a broad-coverage computational model of prediction. This involved developing a grammatical formalism for representing predictions explicitly (using a variant of tree-adjoining grammar). Based on this, we then designed a parsing algorithm for this formalism, along with a lexicon induction scheme and a probabilistic model.
(3) We used the Dundee eye-tracking corpus to test the broad coverage aspects of the model, i.e., its performance on naturally occurring, unrestricted text. We also conducted a total of five eye-tracking experiments to test fine-grained predictions of the model.
Effective start/end date1/05/0530/11/09


  • EPSRC: £121,802.00


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