Paper: Exploring the Data-Driven Prediction of Prepositions in English

ACL ID C10-2031
Title Exploring the Data-Driven Prediction of Prepositions in English
Venue International Conference on Computational Linguistics
Session Poster Session
Year 2010
Authors

Prepositions in English are a well-known challenge for language learners, and the computational analysis of preposition us- age has attracted significant attention. Such research generally starts out by de- veloping models of preposition usage for native English based on a range of fea- tures, from shallow surface evidence to deep linguistically-informed properties. While we agree that ultimately a com- bination of shallow and deep features is needed to balance the preciseness of ex- emplars with the usefulness of generaliza- tions to avoid data sparsity, in this paper we explore the limits of a purely surface- based prediction of prepositions. Using a web-as-corpus approach, we in- vestigate the classification based solely on the relative number of occurrences for tar- get n-grams varying...