2003 MaxEntForFrameNetClassification
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- (Fleischman et al., 2003) ⇒ Michael Fleischman, Namhee Kwon, and Eduard Hovy. (2003). “Maximum Entropy Models for FrameNet Classification.” In: Proceedings of EMNLP 2003 Conference (EMNLP 2003).
Subject Headings: Semantic Role Labeling, FrameNet
Notes
Cited By
- ~49 …
2004
- (Kwon et al., 2004) ⇒ N. Kwon, M. Fleischmann and Eduard Hovy. (2004). “FrameNet-based Semantic Parsing using Maximum Entropy Models.” In: Proceedings of COLING-2004. (paper.pdf)
- QUOTE: Fleischman et al.(FKH, 2003) extend G & J’s work and achieve better performance in role classification for correct frame element boundaries. Their work improves accuracy from 78.5% to 84.7%. The main reasons for improvement are first the use of Maximum Entropy and second the use of sentence-wide features such as Syntactic patterns and previously identified frame element roles. It is not surprising that there is a dependency between each constituent’s role in a sentence and sentence level features reflecting this dependency improve the performance.
Quotes
Abstract
The development of FrameNet, a large database of semantically annotated sentences, has primed research into statistical methods for semantic tagging. We advance previous work by adopting a Maximum Entropy approach and by using Viterbi search to find the highest probability tag sequence for a given sentence. Further we examine the use of syntactic pattern based re-ranking to further increase performance. We analyze our strategy using both extracted and human generated syntactic features. Experiments indicate 85.7% accuracy using human annotations on a held out test set.
References
- Daniel Gildea, Daniel Jurafsky, Automatic labeling of semantic roles, Computational Linguistics, v.28 n.3, p.245-288, September 2002,
| Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
|---|---|---|---|---|---|---|---|---|---|---|
| 2003 MaxEntForFrameNetClassification | Eduard Hovy Namhee Kwon Michael Fleischman | Maximum Entropy Models for FrameNet Classification | Proceedings of EMNLP 2003 Conference | http://acl.ldc.upenn.edu/W/W03/W03-1007.pdf | 2003 |