Abstract
We propose an efficient method to disambiguate English nouns using scene information as context. Recent research directions into context dependent analysis point out the difficulty of defining context and acquiring knowledge. Another problem is the efficiency of resolving semantic constraints. To resolve these problems, we use knowledge from a pictorial dictionary available on the market. It provides spatialscene information as extra-lingual knowledge required for discourse analysis. One of its targets is to disambiguate words. We compared our method with random search approach on a narrative story. The experimental analysis supports that the worddisambiguating speed with our method is over 1.5 times faster than that with the random search. Also it indicates that the disambiguating rate with our method is 83%, higher than that with the random search (51%). We discuss the importance of the representational type for the scene information, evaluate our method's limits, and argue future technologies required to analyze the spatial-scene.
