Paper: Probabilistic Parsing Action Models for Multi-Lingual Dependency Parsing

ACL ID D07-1098
Title Probabilistic Parsing Action Models for Multi-Lingual Dependency Parsing
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2007
Authors

Deterministic dependency parsers use pars- ing actions to construct dependencies. These parsers do not compute the probabil- ity of the whole dependency tree. They only determine parsing actions stepwisely by a trained classifier. To globally model parsing actions of all steps that are taken on the input sentence, we propose two kinds of probabilistic parsing action models that can compute the probability of the whole dependency tree. The tree with the maxi- mal probability is outputted. The experi- ments are carried on 10 languages, and the results show that our probabilistic parsing action models outperform the original de- terministic dependency parser.