In this paper, we propose a new parsing method which extends the rule based parsing scheme that is strong but crispy by adding a probabilistic scheme to deal with peculiar linguistic phenomena of Korean, a partially free order language. Grammar rules are augmented by the extended case frame structure with probabilistic qualifying-restrictions for fillers and a graded matching scheme of probabilistic nature. An incremental probabilistic learning algorithm is provided to obtain the probabilistic qualifying-restriction for each slot of a case frame from a set of training sentences.
Experimental results show that the learning algorithm acquires reliable case frames.
With the reliable case frames and a rather fine-grained and sophisticated matching scheme, this method shows good performance in resolving the case alignment ambiguity in parsing Korean. Keywords Parsing Korean, Case Alignment Problem, Case Frame, Graded Match, Probabilistic Learning. Back to previous page. Back to home page.