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We apply Support Vector Machines (SVMs) to identify English base phrases (chunks). SVMs are known to achieve high generalization perfor- mance even with input data of high dimensional feature spaces. …...

The Stanford-CS224N system is an ensemble of sim- ple classifiers. The first-tier systems are heteroge- neous, consisting primarily of naive-Bayes variants, but also including vector space, memory-based, and other classifier …...

. This paper proposes an approach to improve statistical word align- ment with ensemble methods. Two ensemble methods are investigated: bagging and cross-validation committees. On these two methods, both weighted …...

. This paper reports about a multi-engine approach for the development of a NER system in Bengali by combining the classifiers such as Maximum Entropy (ME), Conditional Random Field (CRF) …...

AbstractCoreference resolution is the task of identifying all mentions in a text that refer to the same real-world entity. Collecting sufficient labelled data from expert annotators to train a high-performance …...