Research in Knowledge Representation for Natural Language Understanding

BBN's ARPA project in Knowledge Representation for Natural Language Understanding is aimed at developing techniques for computer assistance to a decision maker in understanding a complex system or situation using natural language control of an intelligence graphics display. The work that we have been doing falls into three classes: fluent natural language understanding in a graphics context - including helpful systems that go beyond mere passive execution of literal instructions, fundamental problems of knowledge representation and use, and abstract parallel algorithms for knowledge base inferential operations. In this report, we will give a brief summary of the activities of this research project during the past year, in particular in the areas of research on parallel algorithms and VLSI, research on the KL-ONE system, and research on natural language understanding. In addition, we document publications written, presentations given and workshops attended.