This paper describes the association of an hierarchical verb lexicon, VerbNet, with a semantically annotated corpus, the Proposition Bank. It focuses on comparisons of the syntactic coverage of the two resources as a method of evaluating their correspondence. Both VerbNet and PropBank have explicit syntactic frames associated with each verb, which allowed an automatic mapping between the two re...

This work presents an algorithm for the unsupervised learning, or induction, of a simple morphology of a natural language. A probabilistic maximum a posteriori model is utilized, which builds hierarchical representations for a set of morphs, which are morpheme-like units discovered from unannotated text corpora. The induced morph lexicon stores parameters related to both the “meaning” and “form...

Scalable approaches to video event recognition are limited by an inability to automatically generate representations of events that encode abstract temporal structure. This paper presents a method in which temporal information is captured by representing events using a lexicon of hierarchical patterns of movement that are mined from large corpora of unannotated video data. These patterns are th...

In order to develop computer systems which can process the content of natural language texts it is necessary to capture the meaning of words in a way which is robust and domain independent. In this article we discuss a particular kind of word representation based on sets of weighted semantic features. We describe how a lexicon of such patterns can be created automatically from a hierarchical co...