Whether empty samples can be added for training PTPCG

[spico197]

Whether empty samples can be added for training PTPCG

[Spico197]

Hi, there. Thanks for the comments.
Since there are no negative samples in the training set, the model cannot well predict N/A event.
Besides, documents without event instances would be removed during pre-processing (for DuEE-fin only).
You can absolutely add an additional N/A event and negative samples with some code adaptation to provide a more accurate N/A instance prediction.

[TinaGioro]

Thanks for replying. I find another problem about what if there are more than one arguments in an argument role. Does the model take that into account?

[Spico197]

Thanks for replying. I find another problem about what if there are more than one arguments in an argument role. Does the model take that into account?

Yes, PTPCG can predict more than one argument for each role. This is a common practice when we participated in LIC'21 (DuEE-fin):

• your data can be formatted as something like below:

"recguid_eventname_eventdict_list": [
  [
    0,
    "EquityPledge",
    {
      "Pledger": ["李云春"],
      "PledgedShares": ["40789194股", "123123股"],
      "Pledgee": ["招商证券股份有限公司"],
      "TotalHoldingShares": ["162103218股"],
      "TotalHoldingRatio": ["11.55%"],
      "TotalPledgedShares": ["86304393股"],
      "StartDate": ["2015年5月7日"],
      "EndDate": ["2016年5月6日"],
      "ReleasedDate": ["2016年5月6日"]
    }
  ]
]

• make code adaptations to fit such a format (e.g. 1) write new features in data helper to keep multi-arg roles ; 2) multi-hot encoding rather than one-hot when calculating role's classification loss)
• important: set unique_role=False when predicting argument roles: predict_span_role(batch_span_emb, unique_role=False)

However, since the other baselines (Doc2EDAG, GIT) are designed on ChFinAnn, they cannot predict many arguments for one role in a single event instance. To make fair comparisons with these systems, we set PTPCG to only predict one argument each time (unique_role=True), and publish the results in our paper.

[TinaGioro]

Thanks for replying. I am trying to modify the code.

[xxllp]

Thanks for replying. I am trying to modify the code.

不知道是否有改好可以跑的代码