On Removing Ambiguity in Text Understanding

This paper discusses how to remove a kind of ambiguity in a text understanding system based on simulation. The system simulates some events mentioned in text on a world model and observes the behavior of the model during the simulation. Through these processes, it can recognize the other events mentioned implicitly. However, in case the system infers plural number of possible world, it can't decide which one is consistent with the context. We deal with such ambiguities. The ambiguities, in some cases, can be removed by considering contextual information. To remove the ambiguities in the simulation, we define three heuristics based on the characters of the explanatory descriptions and propose an algorithm of "looking ahead". We implement ,ani experimental system. Accqrding to the ,algorithm, the system finds out the supplementary descriptions in the following sentences and removes the ambiguities by using the contents of the supplementary descriptions.