Linguistic Knowledge Acquisition from Parsing Failures

A semi-automatic procedure of linguistic knowledge acquisition is proposed, which combines corpus-based techniques with the conventional rule-based approach. The rule-based component generates all the possible hypotheses of defects which the existing linguistic knowledge might contain, when it fails to parse a sentence. The rule-based component does not try to identify the defects, but generates a set of hypotheses and the corpus-based component chooses the plausible ones among them. The procedure will be used for adapting or re-using existing linguistic resources for new application domains.