Statistical relational learning of natural language.

This project wants to investigate how techniques of statistical relational learning can be used for natural language processing. The focus will be on challenging natural langauge processing tasks, such as semantic role labeling, where syntac and semantic depedencies, structured and unstructured data, local and global models, and probabilistic and logical information must be combined with one another. For what concerns statistical relational learning, the emphasis will lie on probabilistic extensions of the programming language Prolog. The project does not only aim at obtaining improved natural language processing techniques but also better algorithms and systems for statistical relational learning.

Keywords:Probabilistic programming, Artificial intelligence, Statistical relational learning, Computational linguistics, Machine learning

Disciplines:Artificial intelligence, Cognitive science and intelligent systems