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Update docs [ci skip]
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@ -187,7 +187,7 @@ more efficient than processing texts one-by-one.
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> ```python
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> texts = ["One document.", "...", "Lots of documents"]
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> for doc in nlp.pipe(texts, batch_size=50):
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> assert doc.is_parsed
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> assert doc.has_annotation("DEP")
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> ```
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| Name | Description |
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@ -205,9 +205,10 @@ acquired from [WordNet](https://wordnet.princeton.edu/).
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spaCy features a fast and accurate syntactic dependency parser, and has a rich
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API for navigating the tree. The parser also powers the sentence boundary
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detection, and lets you iterate over base noun phrases, or "chunks". You can
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check whether a [`Doc`](/api/doc) object has been parsed with the
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`doc.is_parsed` attribute, which returns a boolean value. If this attribute is
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`False`, the default sentence iterator will raise an exception.
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check whether a [`Doc`](/api/doc) object has been parsed by calling
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`doc.has_annotation("DEP")`, which checks whether the attribute `Token.dep` has
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been set returns a boolean value. If the result is `False`, the default sentence
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iterator will raise an exception.
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<Infobox title="Dependency label scheme" emoji="📖">
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@ -1705,9 +1706,10 @@ and can still be overwritten by the parser.
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<Infobox title="Important note" variant="warning">
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To prevent inconsistent state, you can only set boundaries **before** a document
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is parsed (and `doc.is_parsed` is `False`). To ensure that your component is
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added in the right place, you can set `before='parser'` or `first=True` when
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adding it to the pipeline using [`nlp.add_pipe`](/api/language#add_pipe).
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is parsed (and `doc.has_annotation("DEP")` is `False`). To ensure that your
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component is added in the right place, you can set `before='parser'` or
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`first=True` when adding it to the pipeline using
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[`nlp.add_pipe`](/api/language#add_pipe).
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</Infobox>
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