In order to keep it simple, we ask you to write an e-mail to [email protected] with [email protected] in Cc. We ask to contribute exactly one approach per e-mail. If you have developed several approaches/ systems, write multiple e-mails, one e-mail for one approach/ system.
We remember our terms:
There are up to 5 submissions from different approaches (systems) allowed per team and per subtask. The submission must be submitted via e-mail. You are allowed to withdraw your submission at anytime until the final deadline (also via e-mail).
You are free to participate only in one subtask or both.
Please read the following e-mail-instructions carefully since we can only accept e-mails following the given instructions:
You have to structure your e-mail in the following way:
[ArgMining22-SharedTask-Subtask
(A or B) ]
team name (
number of appraoch)
(the number of approach is an incrementing number starting with 1 to identify this submission. If you just submit one approach/ submission (per subtask), it's just [ArgMining22-SharedTask-Subtask
(A or B) ]
team name (1)
. However, let's say you submit your already third approach for subtask A, the subject should be [ArgMining22-SharedTask-Subtask A]
team name (3)
.)
Please provide a list of information containing the following information in the following order:
- The name of your team (if you submit without having a team, you can write your name here)
- All team members' full names and e-mail addresses, separated by a comma. The first name in the list should be the main contact person
- (optional: the affiliation of each team member)
- the name/ short title of your approach
Please describe in 5-10 sentences your approach/ system.
If you used additional [training] data (data differing from the given training data and/or evaluation data), please descibe here:
- the source(s) of the additional data (links). If the data was artificially generated, please describe (shortly) the generation process instead.
- how you used the data for this task
Only 1 single csv file (please ensure an uft-8-encoding)! Don't use an archive file (hence, no .zip files)!
The csv file should contain the predictions for the test data and should be structured as follows:
topic, Premise, Conclusion, predicted validity, predicted novelty
The predicted validity/ novelty has to be either -1
(not valid/ novel) or 1
(valid/ novel). No floating numbers!
topic, Premise, Conclusion 1, Conclusion 2, predicted validity, predicted novelty
The predicted validity/ novelty has to be either -1
(conclusion 1 outperforms) or 0
(tie) or 1
(conclusion 2 outperforms). No floating numbers!