mirror of https://github.com/explosion/spaCy.git
160 lines
4.4 KiB
Plaintext
160 lines
4.4 KiB
Plaintext
//- 💫 DOCS > API > GOLDPARSE
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include ../../_includes/_mixins
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p Collection for training annotations.
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+h(2, "init") GoldParse.__init__
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+tag method
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p Create a GoldParse.
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code doc]
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+cell #[code Doc]
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+cell The document the annotations refer to.
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+row
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+cell #[code words]
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+cell iterable
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+cell A sequence of unicode word strings.
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+row
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+cell #[code tags]
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+cell iterable
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+cell A sequence of strings, representing tag annotations.
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+row
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+cell #[code heads]
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+cell iterable
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+cell A sequence of integers, representing syntactic head offsets.
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+row
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+cell #[code deps]
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+cell iterable
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+cell A sequence of strings, representing the syntactic relation types.
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+row
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+cell #[code entities]
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+cell iterable
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+cell A sequence of named entity annotations, either as BILUO tag strings, or as #[code (start_char, end_char, label)] tuples, representing the entity positions.
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+footrow
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+cell returns
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+cell #[code GoldParse]
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+cell The newly constructed object.
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+h(2, "len") GoldParse.__len__
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+tag method
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p Get the number of gold-standard tokens.
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+table(["Name", "Type", "Description"])
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+footrow
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+cell returns
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+cell int
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+cell The number of gold-standard tokens.
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+h(2, "is_projective") GoldParse.is_projective
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+tag property
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p
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| Whether the provided syntactic annotations form a projective dependency
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| tree.
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+table(["Name", "Type", "Description"])
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+footrow
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+cell returns
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+cell bool
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+cell Whether annotations form projective tree.
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+h(2, "attributes") Attributes
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code tags]
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+cell list
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+cell The part-of-speech tag annotations.
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+row
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+cell #[code heads]
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+cell list
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+cell The syntactic head annotations.
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+row
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+cell #[code labels]
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+cell list
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+cell The syntactic relation-type annotations.
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+row
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+cell #[code ents]
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+cell list
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+cell The named entity annotations.
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+row
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+cell #[code cand_to_gold]
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+cell list
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+cell The alignment from candidate tokenization to gold tokenization.
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+row
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+cell #[code gold_to_cand]
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+cell list
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+cell The alignment from gold tokenization to candidate tokenization.
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+h(2, "util") Utilities
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+h(3, "biluo_tags_from_offsets") gold.biluo_tags_from_offsets
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+tag function
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p
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| Encode labelled spans into per-token tags, using the
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| #[+a("/docs/api/annotation#biluo") BILUO scheme] (Begin/In/Last/Unit/Out).
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p
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| Returns a list of unicode strings, describing the tags. Each tag string
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| will be of the form either #[code ""], #[code "O"] or
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| #[code "{action}-{label}"], where action is one of #[code "B"],
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| #[code "I"], #[code "L"], #[code "U"]. The string #[code "-"]
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| is used where the entity offsets don't align with the tokenization in the
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| #[code Doc] object. The training algorithm will view these as missing
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| values. #[code O] denotes a non-entity token. #[code B] denotes the
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| beginning of a multi-token entity, #[code I] the inside of an entity
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| of three or more tokens, and #[code L] the end of an entity of two or
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| more tokens. #[code U] denotes a single-token entity.
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+aside-code("Example").
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from spacy.gold import biluo_tags_from_offsets
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text = 'I like London.'
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entities = [(len('I like '), len('I like London'), 'LOC')]
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doc = tokenizer(text)
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tags = biluo_tags_from_offsets(doc, entities)
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assert tags == ['O', 'O', 'U-LOC', 'O']
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code doc]
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+cell #[code Doc]
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+cell
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| The document that the entity offsets refer to. The output tags
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| will refer to the token boundaries within the document.
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+row
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+cell #[code entities]
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+cell iterable
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+cell
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| A sequence of #[code (start, end, label)] triples. #[code start]
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| and #[code end] should be character-offset integers denoting the
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| slice into the original string.
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+footrow
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+cell returns
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+cell list
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+cell
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| Unicode strings, describing the
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| #[+a("/docs/api/annotation#biluo") BILUO] tags.
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