A Novel Disambiguation Method for Unification-Based Grammars Using Probabilistic Context-Free Approximations

We present a novel disambiguation method for unification-based grammars (UBGs). In contrast to other methods, our approach obviates the need for probability models on the UBG side in that it shifts the responsibility to simpler context-free models, indirectly obtained from the UBG. Our approach has three advantages: (i) training can be effectively done in practice, (ii) parsing and disambiguation of context-free readings requires only cubic time, and (iii) involved probability distributions are mathematically clean. In an experiment for a mid-size UBG, we show that our novel approach is feasible. Using unsupervised training, we achieve 88% accuracy on an exact-match task.

• Type: Journal
• Year: 2002
• Where: COLING
• Authors: Bernd Kiefer, Hans-Ulrich Krieger, Detlef Prescher
• Keywords: COLING 2002, COLING 2008, Probability Models, Simpler Context-free Models, Unification-based Grammars