Abstract. One of issues in the bootstrapping for named entity recognition is how to control annotation errors introduced at every iteration. In this paper, we present several heuri...
Active learning is a proven method for reducing the cost of creating the training sets that are necessary for statistical NLP. However, there has been little work on stopping crit...
In this paper, we propose two indepentent solutions to resolve the problems of many different spelling variants and of lack of annotated corpus for training, which are two main di...
This paper addresses the problem of Named Entity Recognition in Query (NERQ), which involves detection of the named entity in a given query and classification of the named entity...
We present a novel hierarchical prior structure for supervised transfer learning in named entity recognition, motivated by the common structure of feature spaces for this task acr...