An increasing number of NLP tasks require semantic labels to be assigned, not only to entities that appear in textual elements, but to the relationships between those entities. In...
This paper explores methods to alleviate the effect of lexical sparseness in the classification of verbal arguments. We show how automatically generated selectional preferences ar...
Ever increasing size of the biomedical literature makes tapping into implicit knowledge in scientific literature a necessity for knowledge discovery. In this paper, a semantic par...
In this paper, we propose a machine learning-based NLP system for automatically creating animated storyboards using the action descriptions of movie scripts. We focus particularly...
We describe a novel neural network architecture for the problem of semantic role labeling. Many current solutions are complicated, consist of several stages and handbuilt features...