Automatically acquired lexicons with subcategorization information have been shown to be accurate and useful for some purposes, but their accuracy still shows room for improvement and their usefulness in many applications remains to be investigated. This paper proposes a two-fold filtering method, which in experiments improved the performance of a Chinese acquisition system remarkably, with an increased precision rate of 76.94% and a recall rate of 83.83%, making the acquired lexicon much more practical for further manual proofreading and other NLP uses. And as far as we know, at the present time, these figures represent the best overall performance achieved in Chinese subcategorization acquisition and in similar researches focusing on other languages.