Proceedings of the Annual Meeting of the Cognitive Science Society

Many parsing strategies for machine translation systems are based entirely on context-free grammars; to try to capture all natural language phenomena, these systems require an overwhelming number of rules; thus a translation system either has limited linguistic coverage, or poor performance (due to formidable grammar size). This paper shows how a principle based "co-routine design" implementation improves the parsing problem for translation. The parser consists of a skeletal structure-building mechanism that operates in conjunction with a linguisticlaly based constraint module, passing control back and forth until underspecified skeltal phrase structure is converted into a fully isntantialed parse tree. The modularity of the parsing design accomodates lingusitic genralization, reduces the grammar size, enables extendibility, and is compatible with studies of human language processing.