Leaderboard
Results
For each essay ID, you must segment the essay into meaningful, coherent units (discourse elements), predict the discourse type label, and predict the discourse effectiveness labels.
Submissions are scored using a custom evaluation metric. You can read more about the evaluation metric here.
The leaderboard reflects submissions evaluated in real time.
| Rank | Team | Score | Number of submissions |
|---|---|---|---|
| 1 | TeamZitao | 0.6636 | 12 |
| 2 | Organizers MS | 0.6446 | 2 |
| 3 | TeamNeroma | 0.6331 | 15 |
| 4 | TeamAndrew | 0.619 | 15 |
| 5 | TeamRaja | 0.6098 | 7 |
| 6 | TeamTrushant | 0.6018 | 12 |
| 7 | TeamTorsten | 0.5859 | 11 |
| 8 | TeamUdbhav | 0.5252 | 13 |
| 9 | Organizers B | 0.44289 | 1 |
| 10 | TeamJames | 0.41257 | 2 |
| 11 | TeamJinnie | 0.40974 | 2 |
| 12 | TeamDeb | 0.2527 | 7 |
| Rank | Team | Recent Score | No. of Submissions | Highest Score |
|---|---|---|---|---|
| 1 | Kkiller ( k.neroma ) | 0.6523 | 49 | 0.6622 |
| 2 | Døge Learner ( h.abedi ) | 0.6290 | 94 | 0.6474 |
| 3 | Catalpa ( andrea1 ) | 0.6253 | 54 | 0.6253 |
| 4 | team CORE-IC ( i.meintanis ) | 0.6210 | 119 | 0.6210 |
| 5 | team 3 TL ( y.maslov ) | 0.5828 | 13 | 0.5829 |
| 6 | pacer ( s.ruseti ) | 0.5085 | 4 | 0.5404 |