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kadarakos 2023-03-27 08:22:17 +00:00
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website/docs/api/spancategorizer.mdx
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@ -20,8 +20,8 @@ output class probabilities are independent for each class. However, if you need
to predict at most one true class for a span, then use `spancat_singlelabel`. It
uses a `Softmax` layer and treats the task as a multi-class problem.
Predicted spans will be saved in a [`SpanGroup`](/api/spangroup) on the doc under `doc.spans[spans_key]`,
where `spans_key` is a component config setting.
Predicted spans will be saved in a [`SpanGroup`](/api/spangroup) on the doc
under `doc.spans[spans_key]`, where `spans_key` is a component config setting.
Individual span scores are stored in `doc.spans[spans_key].attrs["scores"]`.
## Assigned Attributes {id="assigned-attributes"}
@ -30,8 +30,9 @@ Predictions will be saved to `Doc.spans[spans_key]` as a
[`SpanGroup`](/api/spangroup). The scores for the spans in the `SpanGroup` will
be saved in `SpanGroup.attrs["scores"]`.
`spans_key` defaults to `"sc"`, but can be passed as a parameter.
The `spancat` component will overwrite any existing spans under the spans key `doc.spans[spans_key]`.
`spans_key` defaults to `"sc"`, but can be passed as a parameter. The `spancat`
component will overwrite any existing spans under the spans key
`doc.spans[spans_key]`.
| Location | Value |
| -------------------------------------- | -------------------------------------------------------- |