A large amount of empirically derived world knowledge is essential for many languageprocessing tasks, to create expectations that can help assess plausibility and guide disambigua...
Name tagging is a critical early stage in many natural language processing pipelines. In this paper we analyze the types of errors produced by a tagger, distinguishing name classi...
We consider the problem of extracting specified types of information from natural language text. To properly analyze the text, we wish to apply semantic (selectional) constraints ...
In practical applications, decoding speed is very important. Modern structured learning technique adopts template based method to extract millions of features. Complicated templat...
We present the first unsupervised approach to the problem of learning a semantic parser, using Markov logic. Our USP system transforms dependency trees into quasi-logical forms, r...