During the 1990s, work in language engineering saw a dramatic increase in the power and sophistication of statistical approaches to natural languge processing (NLP), along with a growth in the recognition that these methods alone cannot meet the full range of demands for applications of NLP. While statistical methods can bring real advatages in robustness and efficiency, they do not provide the precise, reliable representations of meaning which more conventional symbolic grammars can supply for natural language. A consistent, fine-grained mapping between form and meaning is of critical importance in some NLP applications. This volume provides an update on the development and application of broad-coverage declarative grammars built on sound linguistic foundations and presents several aspects of international research efforts to produce comprehensive, re-usable grammars and efficient technology for parsing and generating with such grammars.