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Hi,
I am trying to compute right-branching and upper bound baselines on the WSJ10 dataset. When I use the code in prpn to evaluation, I get 56.68 (right-branching) and 84.06 (upper bound), different from 61.7(RBranch) 88.1(upper bound) in the paper. But when I use EvalB to do the evaluation, I get 61.7(RBranch) 88.1(upper bound).
So is that mean the way to evaluate the right-branching structure is different from prpn model? Could you please show the right way to compute right-branching and upper bound baselines on the WSJ10 dataset?
Thanks,
Yunfan
The text was updated successfully, but these errors were encountered:
I think the discrepancy is due to sentence-level F1 (adopted by PRPN) vs corpus-level F1 (adopted by EVALB and previous works). Thus the numbers are not exactly comparable, though they are in the general ballpark. There does seem to be a lack of consistency across grammar induction papers (preprocessing, evaluation metric, including sentence-level span vs not, etc.) to make inter-paper comparison difficult to say the least.
Quick question, what did you get for the right branching baselines on the entire dataset?
Hi,
I am trying to compute right-branching and upper bound baselines on the WSJ10 dataset. When I use the code in prpn to evaluation, I get 56.68 (right-branching) and 84.06 (upper bound), different from 61.7(RBranch) 88.1(upper bound) in the paper. But when I use EvalB to do the evaluation, I get 61.7(RBranch) 88.1(upper bound).
So is that mean the way to evaluate the right-branching structure is different from prpn model? Could you please show the right way to compute right-branching and upper bound baselines on the WSJ10 dataset?
Thanks,
Yunfan
The text was updated successfully, but these errors were encountered: