Semantic Role Labeling (State of the art)
Jump to navigation
Jump to search
The printable version is no longer supported and may have rendering errors. Please update your browser bookmarks and please use the default browser print function instead.
Top three results on the WSJ + Brown data from CoNLL 2005 Shared task. More information at (Carreras and Màrquez)
| System Name | Short Description | Main Publications | Software (if available) | Results | Comments (i.e. extra resources used, train/test times, ...) |
|---|---|---|---|---|---|
| SNoW SRL | SNoW, ILP | Punyakanok, et. al. | Illinois SRL software, Illinois SRL demo | 77.92 % | |
| Pradhan | SVM | Pradhan et. al. | ?? | 77.30 | |
| Haghighi | MaxEnt | Haghighi, et. al. | ?? | 77.04 % |
References
- Carreras and Màrquez. Introduction to the CoNLL-2005 Shared Task: Semantic Role Labeling.
- Punyanok et. al. Generalized Inference with Multiple Semantic Role Labeling Systems.
- Pradhan et. al. Semantic Role Chunking Combining Complementary Syntactic Views.
- Haghighi et. al. A Joint Model for Semantic Role Labeling.