Hedge detection using the RelHunter approach
CoNLL '10: Shared Task Proceedings of the Fourteenth Conference on Computational Natural Language Learning --- Shared Task
Learning predicate insertion rules for document abstracting
CICLing'11 Proceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part II
A machine learning approach to Portuguese clause identification
PROPOR'10 Proceedings of the 9th international conference on Computational Processing of the Portuguese Language
ETL ensembles for chunking, NER and SRL
CICLing'10 Proceedings of the 11th international conference on Computational Linguistics and Intelligent Text Processing
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Entropy Guided Transformation Learning (ETL) is a machine learning strategy that extends Transformation Based Learning by providing automatic template generation. In this work, we propose an ETL approach to the clause identification task. We use the English language corpus of the CoNLL'2001 shared task. The achieved performance is not competitive yet, since the F1 of the ETL based system is 80.55, whereas the state-of-the-art system performance is 85.03. Nevertheless, our modeling strategy is very simple, when compared to the state-of-the-art approaches. These first findings indicate that the ETL approach is a promising one for this task. One can enhance its performance by incorporating problem specific knowledge. Additional features can be easily introduced in the ETL model.