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prettier
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@ -475,7 +475,7 @@ report span characteristics such as the average span length and the span (or
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span boundary) distinctiveness. The distinctiveness measure shows how different
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the tokens are with respect to the rest of the corpus using the KL-divergence of
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the token distributions. To learn more, you can check out Papay et al.'s work on
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[*Dissecting Span Identification Tasks with Performance Prediction* (EMNLP 2020)](https://aclanthology.org/2020.emnlp-main.396/).
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[_Dissecting Span Identification Tasks with Performance Prediction_ (EMNLP 2020)](https://aclanthology.org/2020.emnlp-main.396/).
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</Infobox>
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@ -1165,13 +1165,14 @@ $ python -m spacy evaluate [model] [data_path] [--output] [--code] [--gold-prepr
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## apply {#apply new="3.5" tag="command"}
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Applies a trained pipeline to data and stores the resulting
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annotated documents in a `DocBin`. The input can be a single file
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or a directory. The recognized input formats are:
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Applies a trained pipeline to data and stores the resulting annotated documents
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in a `DocBin`. The input can be a single file or a directory. The recognized
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input formats are:
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1. `.spacy`
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2. `.jsonl` containing a user specified `text_key`
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3. Files with any other extension are assumed to be plain text files containing a single document.
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3. Files with any other extension are assumed to be plain text files containing
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a single document.
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When a directory is provided it is traversed recursively to collect all files.
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@ -1218,7 +1219,6 @@ be provided.
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> $ python -m spacy find-threshold my_nlp data.spacy spancat threshold spans_sc_f
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> ```
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| Name | Description |
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| ----------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
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| `model` | Pipeline to evaluate. Can be a package or a path to a data directory. ~~str (positional)~~ |
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