CoNLL-2003 English Named Entity Recognition.
NER challenge for CoNLL-2003 English. Annotations were taken from University of Antwerp. The English data is a collection of news wire articles from the Reuters Corpus, RCV1. [ver. 1.0.0]
This is a long list of all submissions, if you want to see only the best, click leaderboard.
| # | submitter | when | ver. | description | dev-0 BIO-F1 | test-A BIO-F1 | |
|---|---|---|---|---|---|---|---|
| 54 | Jesika Sosnowska | 2023-06-22 04:20 | 1.0.0 | s424452 | N/A | N/A | |
| 53 | Jesika Sosnowska | 2023-06-22 03:32 | 1.0.0 | s424452 | N/A | N/A | |
| 19 | Malinowski | 2023-06-22 00:15 | 1.0.0 | solution | 0.67205 | 0.60862 | |
| 9 | Serba | 2023-06-21 11:01 | 1.0.0 | flair-pre | 0.95300 | 0.91590 | |
| 52 | Jesika Sosnowska | 2023-06-21 10:48 | 1.0.0 | s424452 | N/A | N/A | |
| 21 | Dawidowicz | 2023-06-21 10:10 | 1.0.0 | Add files via upload | 0.68700 | 0.60547 | |
| 24 | Wawrzyniak | 2023-06-21 08:23 | 1.0.0 | LSTM model | 0.65932 | 0.55288 | |
| 18 | Pluciński | 2023-06-20 21:42 | 1.0.0 | solution2 | 0.67086 | 0.61453 | |
| 51 | Pluciński | 2023-06-20 21:38 | 1.0.0 | solution | 0.67086 | N/A | |
| 1 | Patyk | 2023-06-20 21:32 | 1.0.0 | ShrekNet | 0.96238 | 0.93918 | |
| 2 | Patyk | 2023-06-20 21:24 | 1.0.0 | ShrekNet | 0.96617 | 0.93893 | |
| 3 | Patyk | 2023-06-20 21:08 | 1.0.0 | ShrekNet | 0.96753 | 0.93835 | |
| 26 | Wawrzyniak | 2023-06-20 20:28 | 1.0.0 | LSTM model | 0.58933 | 0.51668 | |
| 25 | Wawrzyniak | 2023-06-20 19:58 | 1.0.0 | LSTM model | 0.59160 | 0.52241 | |
| 50 | Wawrzyniak | 2023-06-20 19:54 | 1.0.0 | LSTM model | N/A | N/A | |
| 49 | Wawrzyniak | 2023-06-20 19:07 | 1.0.0 | LSTM model | N/A | N/A | |
| 48 | Szyszko | 2023-06-20 18:05 | 1.0.0 | Solution | N/A | N/A | |
| 5 | Patyk | 2023-06-20 15:11 | 1.0.0 | ShrekNet | 0.96041 | 0.93306 | |
| 4 | Patyk | 2023-06-20 13:15 | 1.0.0 | ShrekNet | 0.96540 | 0.93691 | |
| 7 | Patyk | 2023-06-20 11:44 | 1.0.0 | ShrekNet | 0.95953 | 0.92642 | |
| 12 | Henyk | 2023-06-20 11:39 | 1.0.0 | Solution based on preprocess + big flair + fixes + postprocess | 0.75308 | 0.80180 | |
| 11 | Patyk | 2023-06-20 11:31 | 1.0.0 | ShrekNet | 0.94848 | 0.91077 | |
| 8 | Patyk | 2023-06-20 11:21 | 1.0.0 | ShrekNet | 0.94405 | 0.92157 | |
| 27 | Henyk | 2023-06-20 09:40 | 1.0.0 | Solution based on preprocess + flair + postprocess | 0.42828 | 0.33561 | |
| 10 | Patyk | 2023-06-19 20:28 | 1.0.0 | ShrekNet | 0.94848 | 0.91077 | |
| 29 | Kielar | 2023-06-19 20:18 | 1.0.0 | Solution | 0.24925 | 0.23656 | |
| 47 | Kielar | 2023-06-19 20:10 | 1.0.0 | Solution | 0.24925 | N/A | |
| 46 | Kielar | 2023-06-19 20:09 | 1.0.0 | Solution 9 | 0.06824 | N/A | |
| 33 | Patyk | 2023-06-19 20:09 | 1.0.0 | ShrekNet | 0.02246 | 0.02062 | |
| 45 | Kielar | 2023-06-19 19:51 | 1.0.0 | Solution 8 | 0.05306 | N/A | |
| 40 | Kielar | 2023-06-19 19:41 | 1.0.0 | Solution 7 | 0.05306 | 0.00000 | |
| 39 | Kielar | 2023-06-19 19:39 | 1.0.0 | Solution 6 | 0.00034 | 0.00000 | |
| 38 | Kielar | 2023-06-19 19:38 | 1.0.0 | Solution 5 | 0.00000 | 0.00000 | |
| 37 | Kielar | 2023-06-19 19:37 | 1.0.0 | Solution 4 | 1.00000 | 0.00000 | |
| 36 | Kielar | 2023-06-19 19:36 | 1.0.0 | Solution 3 | 0.00000 | 0.00000 | |
| 35 | Kielar | 2023-06-19 19:34 | 1.0.0 | Solution 2 | N/A | 0.00000 | |
| 34 | Kielar | 2023-06-19 19:27 | 1.0.0 | Solution | N/A | 0.00000 | |
| 6 | Patyk | 2023-06-19 16:54 | 1.0.0 | ShrekNet | 0.96874 | 0.92858 | |
| 44 | Wawrzyniak | 2023-06-19 14:59 | 1.0.0 | LSTM model | N/A | N/A | |
| 43 | Wawrzyniak | 2023-06-19 14:51 | 1.0.0 | LSTM model | N/A | N/A | |
| 42 | Wawrzyniak | 2023-06-19 14:45 | 1.0.0 | LSTM model | N/A | N/A | |
| 41 | Wawrzyniak | 2023-06-19 14:04 | 1.0.0 | LSTM model | N/A | N/A | |
| 30 | Skórzewski | 2023-06-14 12:41 | 1.0.0 | Pairs of capitalized words as 'B-PER I-PER' | 0.23458 | 0.20767 | |
| 31 | Skórzewski | 2023-06-14 12:32 | 1.0.0 | Capitalized words as B-LOC, other words as O | 0.18618 | 0.17285 | |
| 20 | s478840 | 2022-06-21 21:54 | 1.0.0 | s478840 lstm | 0.71273 | 0.60701 | |
| 17 | Jakub Eichner | 2022-06-20 18:11 | 1.0.0 | s478874 neural-network simple | 0.72479 | 0.61718 | |
| 15 | [anonymized] | 2022-06-12 15:50 | 1.0.0 | s478841 neural-network simple | 0.72479 | 0.61816 | |
| 14 | [anonymized] | 2022-06-12 01:53 | 1.0.0 | More training neural-network simple | 0.72479 | 0.61816 | |
| 23 | [anonymized] | 2022-06-12 01:13 | 1.0.0 | Model training mod neural-network simple | 0.67911 | 0.59569 | |
| 32 | [anonymized] | 2022-06-11 23:06 | 1.0.0 | Additional features extraction mod neural-network simple | 0.06108 | 0.05268 | |
| 28 | [anonymized] | 2022-06-11 22:43 | 1.0.0 | Inference results neural-network simple | 0.24069 | 0.25478 | |
| 16 | Mikołaj Pokrywka | 2022-06-07 19:56 | 1.0.0 | s444463 neural-network simple | 0.72678 | 0.61718 | |
| 13 | ked | 2022-06-05 09:22 | 1.0.0 | s449288 - simple NN neural-network simple | 0.69219 | 0.67651 | |
| 22 | Mikołaj Pokrywka | 2022-05-30 21:15 | 1.0.0 | s444463 neural-network simple | 0.71325 | 0.59583 |