Understanding Natural Language Descriptions of Physical Phenomena

The fact that human readers can learn about the physical world from textual descriptions leads to a number of interesting questions about the connections between our conceptual understanding of the physical world and how it is reflected in natural language. This thesis investigates some forms in which information about physical phenomena is typically expressed in natural language and how this knowledge can be used to construct models of the underlying physical processes. Based on an analysis of the representations of physical quantities in natural language and common, reoccurring syntactic patterns, we implemented a system that uses Qualitative Process (QP) Theory to guide the semantic interpretation process to capture information about physical phenomena found in natural language text. We have recast QP Theory in terms of frame semantics as FrameNet-compatible representations (QP frames) and use an extendable, controlled subset of English to capture QP specific information from natural language descriptions. In addition to general background knowledge based on a subset of the Cyc knowledge base and the lexical information supplied by a syntactic parser, the semantics of QP Theory are used in rules that guide the semantic interpretation process and the construction of QP Frames. The thesis illustrates that QP Theory, as an established theoretical framework for handling continuous parameters and causation, can provide an essential component of natural language semantics. Report Documentation Page Form Approved