Abstract
We propose a method to detect metaphoricity between words with probabilistic measurements. In order to detect metaphoricity, we have introduced two probabilistic measurements: “salience gap” and “novelty.” The salience gap measures strength of closed-up property set between a concept pair and has contribution to separate concept pairs into anomalous and others. The measurement can be computed by probabilities of properties in each concept representation. The novelty measures how surprisingly a concept combination is, and contributes to extract anomalous relation rom concept pairs. The measurement can be calculated using word similarity. Using both measurements, concept pairs can be classified into metaphorical, literal and anomalous. For the evaluation of our metaphoricity detection model, we have used one-year newspaper articles and 100 sets of word combinations including three kinds of relations: metaphorical, literal and anomalous. In the experimental results, precision attained 70 percent for dividing metaphorical word pairs from others. It can be considered that performance of our method is useful.
