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Abstract
We explored the problem of achieving in-depth understanding of natural language sentences from narrative technical reports through knowledge-based free text understanding. We rely on the assumption that texts in an expert domain convey much implicit information, which can be recovered by building and reasoning on a model of the situation described with the help of both linguistic and detailed world knowledge. We describe a two-step approach to semantic analysis: the first step assembles a conceptual representation of a sentence and deals with linguistic issues; the second step actually builds and runs the situational model and is totally dedicated to representation and inference. We evaluated this approach by designing a research prototype that processes sentences from clinical narratives in a medical specialty. This prototype was fully implemented and was tested on actual sentences. We hereby give a detailed account of this implementation as well as the first results obtained.