Name
Title | ||
|---|---|---|
A novel disambiguation method for unification-based grammars using probabilistic context-free approximations |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.3115/1072228.1072303 | COLING |
Keywords | Field | DocType |
unification-based grammar,novel approach,novel disambiguation method,involved probability distribution,probabilistic context-free approximation,context-free reading,ubg side,probability model,mid-size ubg,simpler context-free model,unsupervised training,cubic time,probability distribution | Rule-based machine translation,Computer science,Unification,Probability distribution,Natural language processing,Artificial intelligence,Probabilistic logic,Parsing | Conference |
Volume | Citations | PageRank |
C02-1 | 3 | 0.41 |
References | Authors | |
12 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bernd Kiefer | 1 | 194 | 25.67 |
| Hans-Ulrich Krieger | 2 | 3 | 0.41 |
| Detlef Prescher | 3 | 219 | 30.24 |