Wide-Coverage NLP with Linguistically Expressive Grammars

In recent years, there has been a lot of research on wide-coverage statistical natural language processing with linguistically expressive grammars such as Combinatory Categorial Grammars (CCG), Head-driven Phrase-Structure Grammars (HPSG), Lexical-Functional Grammars (LFG) and Tree-Adjoining Grammars (TAG). But although many young researchers in natural language processing are very well trained in machine learning and statistical methods, they often lack the necessary background to understand the linguistic motivation behind these formalisms. Furthermore, in many linguistics departments, syntax is still taught from a purely Chomskian perspective. Additionally, research on these formalisms often takes place within tightly-knit, formalismspecific subcommunities. It is therefore often difficult for outsiders as well as experts to grasp the commonalities of and differences between these formalisms.