Building a large ontology for machine translation

This paper describes efforts underway to construct a largescale ontology to support semantic processing in the PAN-GLOSS knowledge-base machine translation system. Because we axe aiming at broad sem~tntic coverage, we are focusing on automatic and semi-automatic methods of knowledge acquisition. Here we report on algorithms for merging complementary online resources, in particular the LDOCE and WordNet dictionaries. We discuss empirical results, and how these results have been incorporated into the PANGLOSS ontology. 1