Resolving PP attachment Ambiguities with Memory-Based Learning

In this paper we describe the application of Memory-Based Learning to the problem of Prepositional Phrase attachment disambiguation. We compare Memory-Based Learning, which stores examples in memory and generalizes by using intelligent similarity metrics, with a number of recently proposed statistical methods that are well suited to large numbers of features. We evaluate our methods on a common benchmark dataset and show that our method compares favorably to previous methods, and is well-suited to incorporating various unconventional representations of word patterns such as value difference metrics and Lexical Space.

[1]  Walter Daelemans,et al.  Memory-based lexical acquisition and processing , 1993, EAMT.

[2]  John Hughes,et al.  Automatically Acquiring a Classification of Words , 1994 .

[3]  Jakub Zavrel,et al.  The Language Environment and Syntactic Word-Class Acquisition. , 1996 .

[4]  David L. Waltz,et al.  Toward memory-based reasoning , 1986, CACM.

[5]  Mats Rooth,et al.  Structural Ambiguity and Lexical Relations , 1991, ACL.

[6]  Alexander Franz.  Learning PP attachment from corpus statistics , 1995, Learning for Natural Language Processing.

[7]  Adwait Ratnaparkhi,et al.  A Maximum Entropy Model for Prepositional Phrase Attachment , 1994, HLT.

[8]  Lyn Frazier,et al.  ON COMPREHENDING SENTENCES: SYNTACTIC PARSING STRATEGIES. , 1979 .

[9]  Beatrice Santorini,et al.  Building a Large Annotated Corpus of English: The Penn Treebank , 1993, CL.

[10]  Walter Daelemans,et al.  Generalization performance of backpropagation learning on a syllabification task , 1992 .

[11]  Walter Daelemans,et al.  Memory-Based Learning: Using Similarity for Smoothing , 1997, ACL.

[12]  Thomas G. Dietterich,et al.  A study of distance-based machine learning algorithms , 1994 .

[13]  Walter Daelemans,et al.  Abstraction Considered Harmful : Lazy Learning of Language Processing , 1996 .

[14]  Michael Collins,et al.  Prepositional Phrase Attachment through a Backed-off Model , 1995, VLC@ACL.

[15]  Hinrich Schütze,et al.  Distributional Part-of-Speech Tagging , 1995, EACL.

[16]  Walter Daelemans,et al.  Unsupervised Discovery of Phonological Categories through Supervised Learning of Morphological Rules , 1996, COLING.

[17]  Claire Cardie,et al.  Automating Feature Set Selection for Case-Based Learning of Linguistic Knowledge , 1996, EMNLP.

[18]  Eric Brill,et al.  A Rule-Based Approach to Prepositional Phrase Attachment Disambiguation , 1994, COLING.

[19]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[20]  R. Shepard,et al.  Toward a universal law of generalization for psychological science. , 1987, Science.

[21]  Sahibsingh A. Dudani.  The Distance-Weighted k-Nearest-Neighbor Rule , 1976, IEEE Transactions on Systems, Man, and Cybernetics.

[22]  David W. Aha,et al.  Instance-Based Learning Algorithms , 1991, Machine Learning.