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42 lines
1.3 KiB
Markdown
42 lines
1.3 KiB
Markdown
---
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title: SentenceRecognizer
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tag: class
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source: spacy/pipeline/pipes.pyx
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new: 3
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---
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A trainable pipeline component for sentence segmentation. For a simpler,
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ruse-based strategy, see the [`Sentencizer`](/api/sentencizer). This class is a
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subclass of `Pipe` and follows the same API. The component is also available via
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the string name `"senter"`. After initialization, it is typically added to the
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processing pipeline using [`nlp.add_pipe`](/api/language#add_pipe).
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## Default config {#config}
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This is the default configuration used to initialize the model powering the
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pipeline component. See the [model architectures](/api/architectures)
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documentation for details on the architectures and their arguments and
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hyperparameters. To learn more about how to customize the config and train
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custom models, check out the [training config](/usage/training#config) docs.
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```python
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https://github.com/explosion/spaCy/blob/develop/spacy/pipeline/defaults/senter_defaults.cfg
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```
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## SentenceRecognizer.\_\_init\_\_ {#init tag="method"}
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Initialize the sentence recognizer.
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> #### Example
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>
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> ```python
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> # Construction via create_pipe
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> senter = nlp.create_pipe("senter")
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>
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> # Construction from class
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> from spacy.pipeline import SentenceRecognizer
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> senter = SentenceRecognizer()
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> ```
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<!-- TODO: document, similar to other trainable pipeline components -->
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