A maximum entropy approach to preposition and determiner selection

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• Rachele De Felice, University of Oxford
• Friday 16 May 2008, 12:00-13:00
• SW01 Computer Laboratory.

If you have a question about this talk, please contact Johanna Geiss.

In this talk, I present a contextual feature-based approach to the automatic acquisition of preposition and determiner models of use. These models can associate prepositions and determiners to their context with 70.12% and 92.15% accuracy respectively for grammatical text. Preliminary experiments on automatic detection of preposition errors in non-native English writing achieve up to 60% precision and recall.

This talk is part of the NLIP Seminar Series series.

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