Abstract
This paper is concerned with the task of preposition generation in the context of a grammar checker. Relevant features for this task can range from lexical features, such as words and their part-of-speech tags in the vicinity of the preposition, to syntactic features that take into account the attachment site of the prepositional phrase (PP), as well as its argument/adjunct distinction. We compare the performance of these different kinds of features in a memory-based learning framework. Experiments show that using PP attachment information can improve preposition generation accuracy on Wall Street Journal texts.
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References
Bitchener, J., Young, S., Cameron, D.: The effect of different types of corrective feedback on esl student writing. Journal of Second Language Writing 14, 191–205 (2005)
Chodorow, M., Tetreault, J., Han, N.R.: Detection of grammatical errors involving prepositions. In: Proc. ACL-SIGSEM Workshop on Prepositions, Prague, Czech Republic (2007)
Eeg-Olofsson, J., Knutsson, O.: Automatic grammar checking for second language learners — the use of prepositions. In: Proc. NoDaLiDa, ReykjavÃk, Iceland (2003)
De Felice, R., Pulman, S.G.: Automatically acquiring models of preposition use. In: Proc. ACL-SIGSEM Workshop on Prepositions, Prague, Czech Republic (2007)
Quirk, R., et al.: A comprehensive grammar of the english language. Longman (1985)
Merlo, P., Esteve Ferrer, E.: The notion of argument in prepositional phrase attachment. Computational Linguistics 32, 341–378 (2006)
Ratnaparkhi, A., Reynar, J., Roukos, S.: A maximum entropy model for prepositional phrase attachment. In: Proc. ARPA Workshop on Human Language Technology, Plainsboro, NJ (1994)
Daelemans, W., van den Bosch, A., Zavrel, J.: Forgetting exceptions is harmful in language learning. Machine Learning 34, 11–41 (1999)
Daelemans, W., van den Bosch, A., Weijters, A.: Igtree: Using trees for compression and classification in lazy learning algorithms. Artificial Intelligence Review 11, 407–423 (1997)
Marcus, M., et al.: The penn treebank: Annotating predicate argument structure. In: Proc. ARPA Workshop on Human Language Technology, Plainsboro, NJ (1994)
Collins, M.: Head-driven statistical models for natural language parsing. Computational Linguistics 29, 589–637 (2003)
Bies, A., et al.: Bracketing guidelines for treebank ii style. Technical Report, University of Pennsylvania, Philadelphia, PA (1995)
Collins, M., Brooks, J.: Prepositional phrase attachment through a backed-off model. In: Proc. 3rd Workshop on Very Large Corpora, Cambridge, MA (1995)
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Lee, J., Knutsson, O. (2008). The Role of PP Attachment in Preposition Generation. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2008. Lecture Notes in Computer Science, vol 4919. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78135-6_55
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DOI: https://doi.org/10.1007/978-3-540-78135-6_55
Publisher Name: Springer, Berlin, Heidelberg
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