Dynamic lexical acquisition is a procedure where the lexicon of an NLP system is updated automatically during sentence analysis. In our system, new words and new attributes are proposed online according to the context of each sentence, and then get accepted or rejected during syntactic analysis. The accepted lexical information is stored in an auxiliary lexicon which can be used in conjunction with the existing dictionary in subsequent processing. In this way, we are able to process sentences with an incomplete lexicon and fill in the missing info without the need of human editing. As the auxiliary lexicons are corpus-based, domain-specific dictionaries can be created automatically by combining the existing dictionary with different auxiliary lexicons. Evaluation shows that this mechanism significantly improves the coverage of our parser.