We propose an approach to natural language inference based on a model of natural logic, which identifies valid inferences by their lexical and syntactic features, without full sem...
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...
We describe and evaluate a new method of automatic seed word selection for unsupervised sentiment classification of product reviews in Chinese. The whole method is unsupervised an...
This paper explores the use of the homotopy method for training a semi-supervised Hidden Markov Model (HMM) used for sequence labeling. We provide a novel polynomial-time algorith...
Various types of structural information e.g., about the type of constructions in which binding constraints apply, or about the structure of names - play a central role in corefere...
Within the area of general-purpose finegrained subjectivity analysis, opinion topic identification has, to date, received little attention due to both the difficulty of the task a...
Word clustering is a conventional and important NLP task, and the literature has suggested two kinds of approaches to this problem. One is based on the distributional similarity a...
We present procedures which pool lexical information estimated from unlabeled data via the Inside-Outside algorithm, with lexical information from a treebank PCFG. The procedures ...