Automatic labeling of semantic roles
Computational Linguistics
Preposition semantic classification via Penn Treebank and FrameNet
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Semantic role labeling of prepositional phrases
ACM Transactions on Asian Language Information Processing (TALIP)
Joint learning of preposition senses and semantic roles of prepositional phrases
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Semantic role labeling using complete syntactic analysis
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
| Hi-index | 0.00 |
Semantic role expresses the underlying relations that an argument has with its governing predicate Prepositional phrase semantic role labeling concentrates on such relations indicated by prepositional phrases Previously, the problem has been formulated as a word sense disambiguation (WSD) problem and contextual words are used as important features In the past years, there has been a growing interests in general semantic role labeling (SRL) Therefore, it would be interesting to compare the previous contextual features with argument related features specifically designed for semantic role labeling In experiments, we showed that the argument related features are much better than the contextual features, improving classification accuracy from 84.96% to 90.25% on a 6 role task and 71.47% to 75.93% on a 33 role task To further investigate dependency between frame elements, we also introduced new features based on semantic frame that consider the governing predicate, preposition, and content phrase at the same time The use of frame based features further improves the accuracy to 91.25% and 83.48% on both tasks respectively In the end, we found that by treating prepositional phrases carefully, the overall performance of a semantic role labeling system can be improved significantly.