Extending a set-theoretic implementation of Montague Semantics to accommodate n-ary transitive verbs.

Natural-language querying of databases remains an important and challenging area. Many approaches have been proposed over many years yet none of them has provided a comprehensive fully-compositional denotational semantics for a large sub-set of natural language, even for querying first-order non-intentional, non-modal, relational databases. One approach, which has made significant progress, is that which is based on Montague Semantics. Various researchers have helped to develop this approach and have demonstrated its viability. However, none have yet shown how to accommodate transitive verbs of arity greater than two. Our thesis is that existing approaches to the implementation of Montague Semantics in modern functional programming languages can be extended to solve this problem. This thesis is proven through the development of a compositional semantics for n-ary transitive verbs (n ≥ 2) and implementation in the Miranda programming environment. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .R69. Source: Masters Abstracts International, Volume: 44-03, page: 1413. Thesis (M.Sc.)--University of Windsor (Canada), 2005

Improved Portability and Parsing through Interactive Acquisition of Semantic Information

This paper presents SPQR (Selectional Pattern Queries and Responses), a module of the PUNDIT text-processing system designed to facilitate the acquisition of domain-specific semantic information, and to improve the accuracy and efficiency of the parser. SPQR operates by interactively and incrementally collecting information about the semantic acceptability of certain lexical co-occurrence patterns (e.g., subject-verbobject) found in partially constructed parses. The module has proved to be a valuable tool for porting PUNDIT to new domains and acquiring essen- tial semantic information about the domains. Preliminary results also indicate that SPQR causes a threefold reduction in the number of parses found, and about a 40% reduction in total parsing tim