We analyze number agreement in English in the version of Situation Semantics I put forth in [1]. We propose two theoretical notions, agreement target situations and relevance of situations. We propose that structural constraints shift the former in a way governed by the latter. Our analysis shows that number agreement reflects our knowledge about the structure of the world and the speaker's interests in the discourse.

A new method for Chinese word segmentation named Conditional F'||'&'||'BMM (Forward and Backward Maximal Matching) which incorporates both bigram statistics (ie., mutual infonllation and difference of t-test between Chinese characters) and linguistic rules for ambiguity resolution is proposed in this paper The key characteristics of this model are the use of: (i) statistics which can be automatically derived from any raw corpus, (ii) a rule base for disambiguation with consistency and controlled size to be built up in a systematic way.

We propose a method to improve search time and space complexity in statistical machine translation architectures, by employing linguistic bracketing information on the source language sentence. It is one of the advantages of the probabilistic formulation that competing translations may be compared and ranked by a. principled measure, but at the same time, optimizing likelihoods over the translation spa.ce dictates heavy search costs. To make statistical architectures practical, heuristics to reduce search computation must be incorporated. An experiment applying our method to a prototype Chinese-English translation system demonstrates substantial improvement.