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EMNLP
2006

Semantic Role Labeling via Instance-Based Learning

10 years 7 months ago
Semantic Role Labeling via Instance-Based Learning
This paper demonstrates two methods to improve the performance of instancebased learning (IBL) algorithms for the problem of Semantic Role Labeling (SRL). Two IBL algorithms are utilized: k-Nearest Neighbor (kNN), and Priority Maximum Likelihood (PML) with a modified back-off combination method. The experimental data are the WSJ23 and Brown Corpus test sets from the CoNLL2005 Shared Task. It is shown that applying the Tree-Based PredicateArgument Recognition Algorithm (PARA) to the data as a preprocessing stage allows kNN and PML to deliver F1:
Chi-san Althon Lin, Tony C. Smith
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2006
Where EMNLP
Authors Chi-san Althon Lin, Tony C. Smith
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