Paper: Measuring Semantic Coverage

ACL ID C96-1016
Title Measuring Semantic Coverage
Venue International Conference on Computational Linguistics
Session Main Conference
Year 1996

The developlnent of natural language processing systems is currently driven to a large extent by measures of knowledge- base size and coverage of individual phe- nomena relative to a corpus. While these measures have led to significant advances for knowledge-lean applications, they do not adequately motivate progress in computational semantics leading to the development of large-scale, general pur- pose NLP systems. In this article, we argue that depth of semantic represen- tation is essential for covering a broad range of phenomena in the computa- tional treatment of language and propose (lepth as an important additional dimen- sion for measuring the semantic cover- age of NLP systems. We propose an operationalization of this measure and show how to characterize an NLP system along the di...