We model + and − as geometric distributions.
5 In 4 While a more sophisticated model of words would be useful if we intended to use this model for natural language generation, the false independence assumptions present here matter less for the task of learning the semantic correspondences because we always condition on w. 5 p( +; α+) = (1 − α+) + −1 α+, where α+ is a field-specific parameter; p( −; α−) is defined analogously.