Given the human propensity to err, a parser must be able to produce accurate analyses for sentences which are deviant according to human standards, yet which we routinely interpret correctly. State-of-the-art probabilistic parsers are generally robust to errors, and they will return analyses for most ungrammatical sentences. However, these robust analyses are not necessarily correct because they do not always reflect the meanings of the ungrammatical sentences. I present a two-stage "error-aware" probabilistic parsing architecture which allows grammatical and ungrammatical sentences to be accurately parsed. I present the results of experiments carried out using the "error-aware" probabilistic parsing architecture and the Penn Treebank.