mirror of https://github.com/explosion/spaCy.git
128 lines
7.1 KiB
Markdown
128 lines
7.1 KiB
Markdown
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---
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title: Tokenizer
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teaser: Segment text into words, punctuations marks etc.
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tag: class
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source: spacy/tokenizer.pyx
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---
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Segment text, and create `Doc` objects with the discovered segment boundaries.
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## Tokenizer.\_\_init\_\_ {#init tag="method"}
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Create a `Tokenizer`, to create `Doc` objects given unicode text.
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> #### Example
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>
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> ```python
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> # Construction 1
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> from spacy.tokenizer import Tokenizer
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> tokenizer = Tokenizer(nlp.vocab)
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>
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> # Construction 2
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> from spacy.lang.en import English
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> tokenizer = English().Defaults.create_tokenizer(nlp)
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> ```
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| Name | Type | Description |
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| ---------------- | ----------- | ----------------------------------------------------------------------------------- |
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| `vocab` | `Vocab` | A storage container for lexical types. |
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| `rules` | dict | Exceptions and special-cases for the tokenizer. |
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| `prefix_search` | callable | A function matching the signature of `re.compile(string).search` to match prefixes. |
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| `suffix_search` | callable | A function matching the signature of `re.compile(string).search` to match suffixes. |
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| `infix_finditer` | callable | A function matching the signature of `re.compile(string).finditer` to find infixes. |
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| `token_match` | callable | A boolean function matching strings to be recognized as tokens. |
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| **RETURNS** | `Tokenizer` | The newly constructed object. |
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## Tokenizer.\_\_call\_\_ {#call tag="method"}
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Tokenize a string.
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> #### Example
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>
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> ```python
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> tokens = tokenizer(u"This is a sentence")
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> assert len(tokens) == 4
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> ```
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| Name | Type | Description |
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| ----------- | ------- | --------------------------------------- |
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| `string` | unicode | The string to tokenize. |
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| **RETURNS** | `Doc` | A container for linguistic annotations. |
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## Tokenizer.pipe {#pipe tag="method"}
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Tokenize a stream of texts.
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> #### Example
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>
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> ```python
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> texts = [u"One document.", u"...", u"Lots of documents"]
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> for doc in tokenizer.pipe(texts, batch_size=50):
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> pass
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> ```
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| Name | Type | Description |
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| ------------ | ----- | ----------------------------------------------------------------------------------------------------------------------- |
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| `texts` | - | A sequence of unicode texts. |
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| `batch_size` | int | The number of texts to accumulate in an internal buffer. |
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| `n_threads` | int | The number of threads to use, if the implementation supports multi-threading. The default tokenizer is single-threaded. |
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| **YIELDS** | `Doc` | A sequence of Doc objects, in order. |
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## Tokenizer.find_infix {#find_infix tag="method"}
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Find internal split points of the string.
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| Name | Type | Description |
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| ----------- | ------- | -------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `string` | unicode | The string to split. |
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| **RETURNS** | list | A list of `re.MatchObject` objects that have `.start()` and `.end()` methods, denoting the placement of internal segment separators, e.g. hyphens. |
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## Tokenizer.find_prefix {#find_prefix tag="method"}
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Find the length of a prefix that should be segmented from the string, or `None`
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if no prefix rules match.
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| Name | Type | Description |
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| ----------- | ------- | ------------------------------------------------------ |
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| `string` | unicode | The string to segment. |
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| **RETURNS** | int | The length of the prefix if present, otherwise `None`. |
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## Tokenizer.find_suffix {#find_suffix tag="method"}
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Find the length of a suffix that should be segmented from the string, or `None`
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if no suffix rules match.
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| Name | Type | Description |
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| ----------- | ------------ | ------------------------------------------------------ |
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| `string` | unicode | The string to segment. |
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| **RETURNS** | int / `None` | The length of the suffix if present, otherwise `None`. |
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## Tokenizer.add_special_case {#add_special_case tag="method"}
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Add a special-case tokenization rule. This mechanism is also used to add custom
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tokenizer exceptions to the language data. See the usage guide on
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[adding languages](/usage/adding-languages#tokenizer-exceptions) for more
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details and examples.
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> #### Example
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>
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> ```python
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> from spacy.attrs import ORTH, LEMMA
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> case = [{"don't": [{ORTH: "do"}, {ORTH: "n't", LEMMA: "not"}]}]
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> tokenizer.add_special_case(case)
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> ```
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| Name | Type | Description |
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| ------------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
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| `string` | unicode | The string to specially tokenize. |
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| `token_attrs` | iterable | A sequence of dicts, where each dict describes a token and its attributes. The `ORTH` fields of the attributes must exactly match the string when they are concatenated. |
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## Attributes {#attributes}
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| Name | Type | Description |
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| ---------------- | ------- | -------------------------------------------------------------------------------------------------------------------------- |
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| `vocab` | `Vocab` | The vocab object of the parent `Doc`. |
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| `prefix_search` | - | A function to find segment boundaries from the start of a string. Returns the length of the segment, or `None`. |
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| `suffix_search` | - | A function to find segment boundaries from the end of a string. Returns the length of the segment, or `None`. |
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| `infix_finditer` | - | A function to find internal segment separators, e.g. hyphens. Returns a (possibly empty) list of `re.MatchObject` objects. |
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