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replace user-facing references to "sbd" with "sentencizer" (#2985)
## Description Fixes #2693 Previously, the tokens `sbd` and `sentencizer` would create the same nlp pipe. Internally, both would be called `sbd`. This setup became problematic because it was hard for a user relying on the `sentencizer` pipe name to realize that their pipe's name would be `sbd` for all functions other than creating a pipe. This PR intends to change the API and API documentation to fully support `sentencizer` and drop any user-facing references to `sbd`. ### Types of change end-user API bug ## Checklist <!--- Before you submit the PR, go over this checklist and make sure you can tick off all the boxes. [] -> [x] --> - [x] I have submitted the spaCy Contributor Agreement. - [x] I ran the tests, and all new and existing tests passed. - [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
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# spaCy contributor agreement
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This spaCy Contributor Agreement (**"SCA"**) is based on the
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[Oracle Contributor Agreement](http://www.oracle.com/technetwork/oca-405177.pdf).
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The SCA applies to any contribution that you make to any product or project
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managed by us (the **"project"**), and sets out the intellectual property rights
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you grant to us in the contributed materials. The term **"us"** shall mean
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[ExplosionAI UG (haftungsbeschränkt)](https://explosion.ai/legal). The term
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**"you"** shall mean the person or entity identified below.
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If you agree to be bound by these terms, fill in the information requested
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below and include the filled-in version with your first pull request, under the
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folder [`.github/contributors/`](/.github/contributors/). The name of the file
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should be your GitHub username, with the extension `.md`. For example, the user
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example_user would create the file `.github/contributors/example_user.md`.
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Read this agreement carefully before signing. These terms and conditions
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constitute a binding legal agreement.
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## Contributor Agreement
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1. The term "contribution" or "contributed materials" means any source code,
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object code, patch, tool, sample, graphic, specification, manual,
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documentation, or any other material posted or submitted by you to the project.
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2. With respect to any worldwide copyrights, or copyright applications and
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registrations, in your contribution:
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* you hereby assign to us joint ownership, and to the extent that such
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assignment is or becomes invalid, ineffective or unenforceable, you hereby
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grant to us a perpetual, irrevocable, non-exclusive, worldwide, no-charge,
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royalty-free, unrestricted license to exercise all rights under those
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copyrights. This includes, at our option, the right to sublicense these same
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rights to third parties through multiple levels of sublicensees or other
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licensing arrangements;
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* you agree that each of us can do all things in relation to your
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contribution as if each of us were the sole owners, and if one of us makes
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a derivative work of your contribution, the one who makes the derivative
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work (or has it made will be the sole owner of that derivative work;
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* you agree that you will not assert any moral rights in your contribution
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against us, our licensees or transferees;
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* you agree that we may register a copyright in your contribution and
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exercise all ownership rights associated with it; and
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* you agree that neither of us has any duty to consult with, obtain the
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consent of, pay or render an accounting to the other for any use or
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distribution of your contribution.
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3. With respect to any patents you own, or that you can license without payment
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to any third party, you hereby grant to us a perpetual, irrevocable,
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non-exclusive, worldwide, no-charge, royalty-free license to:
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* make, have made, use, sell, offer to sell, import, and otherwise transfer
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your contribution in whole or in part, alone or in combination with or
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included in any product, work or materials arising out of the project to
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which your contribution was submitted, and
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* at our option, to sublicense these same rights to third parties through
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multiple levels of sublicensees or other licensing arrangements.
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4. Except as set out above, you keep all right, title, and interest in your
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contribution. The rights that you grant to us under these terms are effective
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on the date you first submitted a contribution to us, even if your submission
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took place before the date you sign these terms.
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5. You covenant, represent, warrant and agree that:
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* Each contribution that you submit is and shall be an original work of
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authorship and you can legally grant the rights set out in this SCA;
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* to the best of your knowledge, each contribution will not violate any
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third party's copyrights, trademarks, patents, or other intellectual
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property rights; and
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* each contribution shall be in compliance with U.S. export control laws and
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other applicable export and import laws. You agree to notify us if you
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become aware of any circumstance which would make any of the foregoing
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representations inaccurate in any respect. We may publicly disclose your
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participation in the project, including the fact that you have signed the SCA.
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6. This SCA is governed by the laws of the State of California and applicable
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U.S. Federal law. Any choice of law rules will not apply.
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7. Please place an “x” on one of the applicable statement below. Please do NOT
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mark both statements:
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* [x] I am signing on behalf of myself as an individual and no other person
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or entity, including my employer, has or will have rights with respect to my
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contributions.
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* [] I am signing on behalf of my employer or a legal entity and I have the
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actual authority to contractually bind that entity.
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## Contributor Details
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| Field | Entry |
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|------------------------------- | -------------------- |
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| Name | Gavriel Loria |
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| Company name (if applicable) | |
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| Title or role (if applicable) | |
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| Date | Nov 29, 2018 |
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| GitHub username | gavrieltal |
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| Website (optional) | |
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@ -284,6 +284,9 @@ class Errors(object):
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E106 = ("Can't find doc._.{attr} attribute specified in the underscore "
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E106 = ("Can't find doc._.{attr} attribute specified in the underscore "
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"settings: {opts}")
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"settings: {opts}")
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E107 = ("Value of doc._.{attr} is not JSON-serializable: {value}")
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E107 = ("Value of doc._.{attr} is not JSON-serializable: {value}")
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E108 = ("As of spaCy v2.1, the pipe name `sbd` has been deprecated "
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"in favor of the pipe name `sentencizer`, which does the same "
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"thing. For example, use `nlp.create_pipeline('sentencizer')`")
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@add_codes
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@add_codes
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@ -116,7 +116,6 @@ class Language(object):
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"ner": lambda nlp, **cfg: EntityRecognizer(nlp.vocab, **cfg),
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"ner": lambda nlp, **cfg: EntityRecognizer(nlp.vocab, **cfg),
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"similarity": lambda nlp, **cfg: SimilarityHook(nlp.vocab, **cfg),
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"similarity": lambda nlp, **cfg: SimilarityHook(nlp.vocab, **cfg),
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"textcat": lambda nlp, **cfg: TextCategorizer(nlp.vocab, **cfg),
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"textcat": lambda nlp, **cfg: TextCategorizer(nlp.vocab, **cfg),
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"sbd": lambda nlp, **cfg: SentenceSegmenter(nlp.vocab, **cfg),
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"sentencizer": lambda nlp, **cfg: SentenceSegmenter(nlp.vocab, **cfg),
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"sentencizer": lambda nlp, **cfg: SentenceSegmenter(nlp.vocab, **cfg),
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"merge_noun_chunks": lambda nlp, **cfg: merge_noun_chunks,
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"merge_noun_chunks": lambda nlp, **cfg: merge_noun_chunks,
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"merge_entities": lambda nlp, **cfg: merge_entities,
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"merge_entities": lambda nlp, **cfg: merge_entities,
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@ -243,7 +242,10 @@ class Language(object):
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RETURNS (callable): Pipeline component.
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RETURNS (callable): Pipeline component.
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"""
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"""
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if name not in self.factories:
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if name not in self.factories:
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raise KeyError(Errors.E002.format(name=name))
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if name == "sbd":
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raise KeyError(Errors.E108.format(name=name))
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else:
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raise KeyError(Errors.E002.format(name=name))
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factory = self.factories[name]
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factory = self.factories[name]
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return factory(self, **config)
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return factory(self, **config)
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@ -49,7 +49,7 @@ class SentenceSegmenter(object):
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Sentence detection strategies should be generators that take `Doc` objects
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Sentence detection strategies should be generators that take `Doc` objects
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and yield `Span` objects for each sentence.
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and yield `Span` objects for each sentence.
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"""
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"""
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name = 'sbd'
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name = 'sentencizer'
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def __init__(self, vocab, strategy=None):
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def __init__(self, vocab, strategy=None):
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self.vocab = vocab
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self.vocab = vocab
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@ -88,8 +88,8 @@ p
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from spacy.lang.en import English
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from spacy.lang.en import English
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nlp = English() # just the language with no model
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nlp = English() # just the language with no model
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sbd = nlp.create_pipe('sentencizer') # or: nlp.create_pipe('sbd')
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sentencizer = nlp.create_pipe('sentencizer')
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nlp.add_pipe(sbd)
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nlp.add_pipe(sentencizer)
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doc = nlp(u"This is a sentence. This is another sentence.")
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doc = nlp(u"This is a sentence. This is another sentence.")
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for sent in doc.sents:
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for sent in doc.sents:
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print(sent.text)
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print(sent.text)
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@ -122,8 +122,8 @@ p
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yield doc[start:len(doc)]
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yield doc[start:len(doc)]
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nlp = English() # just the language with no model
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nlp = English() # just the language with no model
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sbd = SentenceSegmenter(nlp.vocab, strategy=split_on_newlines)
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sentencizer = SentenceSegmenter(nlp.vocab, strategy=split_on_newlines)
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nlp.add_pipe(sbd)
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nlp.add_pipe(sentencizer)
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doc = nlp(u"This is a sentence\n\nThis is another sentence\nAnd more")
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doc = nlp(u"This is a sentence\n\nThis is another sentence\nAnd more")
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for sent in doc.sents:
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for sent in doc.sents:
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print([token.text for token in sent])
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print([token.text for token in sent])
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@ -144,7 +144,7 @@ p
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+code-exec.
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+code-exec.
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import spacy
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import spacy
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def sbd_component(doc):
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def custom_sentencizer(doc):
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for i, token in enumerate(doc[:-2]):
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for i, token in enumerate(doc[:-2]):
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# define sentence start if period + titlecase token
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# define sentence start if period + titlecase token
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if token.text == '.' and doc[i+1].is_title:
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if token.text == '.' and doc[i+1].is_title:
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@ -152,7 +152,7 @@ p
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return doc
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return doc
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nlp = spacy.load('en_core_web_sm')
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nlp = spacy.load('en_core_web_sm')
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nlp.add_pipe(sbd_component, before='parser') # insert before the parser
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nlp.add_pipe(custom_sentencizer, before='parser') # insert before parser
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doc = nlp(u"This is a sentence. This is another sentence.")
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doc = nlp(u"This is a sentence. This is another sentence.")
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for sent in doc.sents:
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for sent in doc.sents:
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print(sent.text)
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print(sent.text)
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