DeSRL: A Linear-Time Semantic Role Labeling System
Source:
CoNLL 2008 Shared Task (2008)
Abstract:
This paper describes the DeSRL system, a joined effort of
Yahoo! Research Barcelona and Universita di Pisa.
The system is characterized by an efficient pipeline of linear
complexity components, each carrying out a different sub-task.
Classifier errors and ambiguities are addressed with several
strategies: revision models, voting, and reranking.
The system participated in the closed challenge
ranking third in the complete problem evaluation with the following
scores: 82.06 labeled macro F1 for the overall task,
86.6 labeled attachment for syntactic dependencies, and 77.5 labeled
F1 for semantic dependencies.
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