MUC-7 (State of the art)
Jump to navigation
Jump to search
- Performance measure: F = 2 * Precision * Recall / (Recall + Precision)
- Precision: percentage of named entities found by the algorithm that are correct
- Recall: percentage of named entities defined in the corpus that were found by the program
- Exact calculation of precision and recall is explained in the MUC scoring software
- Training data: Training section of MUC-7 dataset
- Testing data: Formal section of MUC-7 dataset
Table of results
| System name | Short description | Main publications | Software | Results (F) |
|---|---|---|---|---|
| Human | Human annotator | MUC-7 proceedings | 97.60% | |
| LTG | Best MUC-7 participant | Mikheev, Grover and Moens (1998) | 93.39% |
References
Mikheev, A., Grover, C., and Moens, M. (1998). Description of the LTG system used for MUC-7. Proceedings of the Seventh Message Understanding Conference (MUC-7). Fairfax, Virginia.