Speaker: Ivan Titov, Senior Researcher,Saarland University,Saarbrücken, Germany.

Language understanding by machines is one of the main objectives of artificial intelligence research. Though full understanding of unrestricted texts is still a remote goal, in recent years, statistical approaches have been developed to predict more shallow forms of semantics, such as underlying predicate-argument structure of sentences. Most existing statistical techniques for tackling these problems rely on large human-annotated datasets, which are expensive to create and exist only for a very limited number of languages. Even then, they are not very robust, cover only a small proportion of semantic constructions appearing in the labeled data, and are domain-dependent...for more info