Paper: Memory-Based Dependency Parsing

ACL ID W04-2407
Title Memory-Based Dependency Parsing
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2004

This paper reports the results of experiments using memory-based learning to guide a de- terministic dependency parser for unrestricted natural language text. Using data from a small treebank of Swedish, memory-based classifiers for predicting the next action of the parser are constructed. The accuracy of a classifier as such is evaluated on held-out data derived from the treebank, and its performance as a parser guide is evaluated by parsing the held-out por- tion of the treebank. The evaluation shows that memory-based learning gives a signficant im- provement over a previous probabilistic model based on maximum conditional likelihood esti- mation and that the inclusion of lexical features improves the accuracy even further.