1. A referring expression processor comprising: a referring expression processing section which performs understanding of referring expressions using a probabilistic model constructed with a referring expression Bayesian network, each referring expression Bayesian network representing relationships between a reference domain (D) which is a set of possible referents, a referent (X) in the reference domain, a concept (C) concerning the referent and a word (W) which represents the concept; and a memory which stores data necessary for constructing the referring expression Bayesian network, wherein the understanding of referring expressions comprises obtaining a probability P(X|W) by obtaining a probability P(D), obtaining a probability P(X|D), obtaining a probability P(C|X,D), obtaining a probability P(W|C,X), obtaining a probability P(W,C,X,D) based on the probability P(D), the probability P(X|D), the probability P(C|X,D), and the probability P(W|C,X), and marginalizing the probability P(W,C,X,D).