Applying System Combination to Base Noun Phrase Identification

TL;DR

This paper demonstrates that combining multiple machine learning algorithms through system combination methods significantly improves base noun phrase identification accuracy, outperforming individual models and previous benchmarks.

Contribution

It introduces a system combination approach using seven classifiers and a majority vote method, achieving state-of-the-art results in base noun phrase identification.

Findings

System combination outperforms individual classifiers.

Majority voting of top systems improves accuracy.

Achieved new best results on a standard dataset.

Abstract

We use seven machine learning algorithms for one task: identifying base noun phrases. The results have been processed by different system combination methods and all of these outperformed the best individual result. We have applied the seven learners with the best combinator, a majority vote of the top five systems, to a standard data set and managed to improve the best published result for this data set.