mirror of https://github.com/explosion/spaCy.git
542 lines
13 KiB
Plaintext
542 lines
13 KiB
Plaintext
//- 💫 DOCS > API > TOKEN
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include ../../_includes/_mixins
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p An individual token — i.e. a word, punctuation symbol, whitespace, etc.
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+h(2, "init") Token.__init__
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+tag method
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p Construct a #[code Token] object.
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+aside-code("Example").
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doc = nlp(u'Give it back! He pleaded.')
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token = doc[0]
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assert token.text == u'Give'
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code vocab]
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+cell #[code Vocab]
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+cell A storage container for lexical types.
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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 parent document.
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+row
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+cell #[code offset]
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+cell int
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+cell The index of the token within the document.
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+footrow
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+cell returns
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+cell #[code Token]
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+cell The newly constructed object.
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+h(2, "len") Token.__len__
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+tag method
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p The number of unicode characters in the token, i.e. #[code token.text].
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+aside-code("Example").
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doc = nlp(u'Give it back! He pleaded.')
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token = doc[0]
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assert len(token) == 4
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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 unicode characters in the token.
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+h(2, "check_flag") Token.check_flag
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+tag method
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p Check the value of a boolean flag.
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+aside-code("Example").
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from spacy.attrs import IS_TITLE
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doc = nlp(u'Give it back! He pleaded.')
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token = doc[0]
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assert token.check_flag(IS_TITLE) == True
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code flag_id]
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+cell int
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+cell The attribute ID of the flag to check.
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+footrow
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+cell returns
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+cell bool
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+cell Whether the flag is set.
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+h(2, "similarity") Token.similarity
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+tag method
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+tag-model("vectors")
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p Compute a semantic similarity estimate. Defaults to cosine over vectors.
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+aside-code("Example").
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apples, _, oranges = nlp(u'apples and oranges')
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apples_oranges = apples.similarity(oranges)
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oranges_apples = oranges.similarity(apples)
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assert apples_oranges == oranges_apples
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+table(["Name", "Type", "Description"])
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+row
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+cell other
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+cell -
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+cell
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| The object to compare with. By default, accepts #[code Doc],
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| #[code Span], #[code Token] and #[code Lexeme] objects.
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+footrow
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+cell returns
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+cell float
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+cell A scalar similarity score. Higher is more similar.
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+h(2, "nbor") Token.nbor
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+tag method
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p Get a neighboring token.
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+aside-code("Example").
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doc = nlp(u'Give it back! He pleaded.')
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give_nbor = doc[0].nbor()
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assert give_nbor.text == u'it'
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+table(["Name", "Type", "Description"])
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+row
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+cell #[code i]
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+cell int
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+cell The relative position of the token to get. Defaults to #[code 1].
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+footrow
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+cell returns
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+cell #[code Token]
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+cell The token at position #[code self.doc[self.i+i]].
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+h(2, "is_ancestor") Token.is_ancestor
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+tag method
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+tag-model("parse")
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p
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| Check whether this token is a parent, grandparent, etc. of another
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| in the dependency tree.
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+aside-code("Example").
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doc = nlp(u'Give it back! He pleaded.')
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give = doc[0]
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it = doc[1]
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assert give.is_ancestor(it)
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+table(["Name", "Type", "Description"])
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+row
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+cell descendant
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+cell #[code Token]
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+cell Another token.
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+footrow
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+cell returns
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+cell bool
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+cell Whether this token is the ancestor of the descendant.
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+h(2, "ancestors") Token.ancestors
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+tag property
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+tag-model("parse")
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p The rightmost token of this token's syntactic descendants.
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+aside-code("Example").
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doc = nlp(u'Give it back! He pleaded.')
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it_ancestors = doc[1].ancestors
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assert [t.text for t in it_ancestors] == [u'Give']
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he_ancestors = doc[4].ancestors
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assert [t.text for t in he_ancestors] == [u'pleaded']
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+table(["Name", "Type", "Description"])
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+footrow
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+cell yields
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+cell #[code Token]
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+cell
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| A sequence of ancestor tokens such that
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| #[code ancestor.is_ancestor(self)].
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+h(2, "conjuncts") Token.conjuncts
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+tag property
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+tag-model("parse")
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p A sequence of coordinated tokens, including the token itself.
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+aside-code("Example").
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doc = nlp(u'I like apples and oranges')
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apples_conjuncts = doc[2].conjuncts
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assert [t.text for t in apples_conjuncts] == [u'oranges']
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+table(["Name", "Type", "Description"])
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+footrow
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+cell yields
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+cell #[code Token]
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+cell A coordinated token.
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+h(2, "children") Token.children
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+tag property
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+tag-model("parse")
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p A sequence of the token's immediate syntactic children.
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+aside-code("Example").
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doc = nlp(u'Give it back! He pleaded.')
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give_children = doc[0].children
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assert [t.text for t in give_children] == [u'it', u'back', u'!']
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+table(["Name", "Type", "Description"])
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+footrow
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+cell yields
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+cell #[code Token]
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+cell A child token such that #[code child.head==self].
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+h(2, "subtree") Token.subtree
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+tag property
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+tag-model("parse")
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p A sequence of all the token's syntactic descendents.
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+aside-code("Example").
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doc = nlp(u'Give it back! He pleaded.')
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give_subtree = doc[0].subtree
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assert [t.text for t in give_subtree] == [u'Give', u'it', u'back', u'!']
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+table(["Name", "Type", "Description"])
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+footrow
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+cell yields
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+cell #[code Token]
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+cell A descendant token such that #[code self.is_ancestor(descendant)].
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+h(2, "has_vector") Token.has_vector
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+tag property
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+tag-model("vectors")
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p
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| A boolean value indicating whether a word vector is associated with the
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| token.
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+aside-code("Example").
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doc = nlp(u'I like apples')
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apples = doc[2]
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assert apples.has_vector
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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 the token has a vector data attached.
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+h(2, "vector") Token.vector
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+tag property
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+tag-model("vectors")
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p A real-valued meaning representation.
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+aside-code("Example").
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doc = nlp(u'I like apples')
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apples = doc[2]
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assert apples.vector.dtype == 'float32'
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assert apples.vector.shape == (300,)
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+table(["Name", "Type", "Description"])
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+footrow
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+cell returns
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+cell #[code numpy.ndarray[ndim=1, dtype='float32']]
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+cell A 1D numpy array representing the token's semantics.
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+h(2, "vector_norm") Span.vector_norm
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+tag property
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+tag-model("vectors")
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p The L2 norm of the token's vector representation.
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+aside-code("Example").
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doc = nlp(u'I like apples and pasta')
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apples = doc[2]
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pasta = doc[4]
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apples.vector_norm # 6.89589786529541
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pasta.vector_norm # 7.759851932525635
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assert apples.vector_norm != pasta.vector_norm
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+table(["Name", "Type", "Description"])
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+footrow
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+cell returns
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+cell float
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+cell The L2 norm of the vector representation.
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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 text]
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+cell unicode
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+cell Verbatim text content.
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+row
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+cell #[code text_with_ws]
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+cell unicode
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+cell Text content, with trailing space character if present.
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+row
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+cell #[code whitespace]
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+cell int
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+cell Trailing space character if present.
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+row
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+cell #[code whitespace_]
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+cell unicode
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+cell Trailing space character if present.
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+row
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+cell #[code vocab]
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+cell #[code Vocab]
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+cell The vocab object of the parent #[code Doc].
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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 parent document.
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+row
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+cell #[code head]
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+cell #[code Token]
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+cell The syntactic parent, or "governor", of this token.
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+row
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+cell #[code left_edge]
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+cell #[code Token]
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+cell The leftmost token of this token's syntactic descendants.
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+row
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+cell #[code right_edge]
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+cell #[code Token]
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+cell The rightmost token of this token's syntactic descendents.
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+row
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+cell #[code i]
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+cell int
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+cell The index of the token within the parent document.
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+row
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+cell #[code ent_type]
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+cell int
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+cell Named entity type.
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+row
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+cell #[code ent_type_]
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+cell unicode
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+cell Named entity type.
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+row
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+cell #[code ent_iob]
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+cell int
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+cell
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| IOB code of named entity tag. #[code "B"]
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| means the token begins an entity, #[code "I"] means it is inside
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| an entity, #[code "O"] means it is outside an entity, and
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| #[code ""] means no entity tag is set.
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+row
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+cell #[code ent_iob_]
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+cell unicode
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+cell
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| IOB code of named entity tag. #[code "B"]
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| means the token begins an entity, #[code "I"] means it is inside
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| an entity, #[code "O"] means it is outside an entity, and
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| #[code ""] means no entity tag is set.
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+row
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+cell #[code ent_id]
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+cell int
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+cell
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| ID of the entity the token is an instance of, if any. Usually
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| assigned by patterns in the Matcher.
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+row
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+cell #[code ent_id_]
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+cell unicode
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+cell
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| ID of the entity the token is an instance of, if any. Usually
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| assigned by patterns in the Matcher.
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+row
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+cell #[code lemma]
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+cell int
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+cell
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| Base form of the word, with no inflectional suffixes.
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+row
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+cell #[code lemma_]
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+cell unicode
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+cell Base form of the word, with no inflectional suffixes.
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+row
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+cell #[code lower]
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+cell int
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+cell Lower-case form of the word.
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+row
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+cell #[code lower_]
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+cell unicode
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+cell Lower-case form of the word.
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+row
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+cell #[code shape]
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+cell int
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+cell Transform of the word's string, to show orthographic features.
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+row
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+cell #[code shape_]
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+cell unicode
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+cell A transform of the word's string, to show orthographic features.
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+row
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+cell #[code prefix]
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+cell int
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+cell Integer ID of a length-N substring from the start of the
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| word. Defaults to #[code N=1].
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+row
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+cell #[code prefix_]
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+cell unicode
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+cell
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| A length-N substring from the start of the word. Defaults to
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| #[code N=1].
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+row
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+cell #[code suffix]
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+cell int
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+cell
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| Length-N substring from the end of the word. Defaults to #[code N=3].
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+row
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+cell #[code suffix_]
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+cell unicode
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+cell Length-N substring from the end of the word. Defaults to #[code N=3].
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+row
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+cell #[code is_alpha]
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+cell bool
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+cell Equivalent to #[code word.orth_.isalpha()].
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+row
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+cell #[code is_ascii]
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+cell bool
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+cell Equivalent to #[code [any(ord(c) >= 128 for c in word.orth_)]].
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+row
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+cell #[code is_digit]
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+cell bool
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+cell Equivalent to #[code word.orth_.isdigit()].
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+row
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+cell #[code is_lower]
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+cell bool
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+cell Equivalent to #[code word.orth_.islower()].
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+row
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+cell #[code is_title]
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+cell bool
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+cell Equivalent to #[code word.orth_.istitle()].
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+row
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+cell #[code is_punct]
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+cell bool
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+cell Equivalent to #[code word.orth_.ispunct()].
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+row
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+cell #[code is_space]
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+cell bool
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+cell Equivalent to #[code word.orth_.isspace()].
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+row
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+cell #[code like_url]
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+cell bool
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+cell Does the word resemble a URL?
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+row
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+cell #[code like_num]
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+cell bool
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+cell Does the word represent a number? e.g. “10.9”, “10”, “ten”, etc.
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+row
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+cell #[code like_email]
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+cell bool
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+cell Does the word resemble an email address?
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+row
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+cell #[code is_oov]
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+cell bool
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+cell Is the word out-of-vocabulary?
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+row
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+cell #[code is_stop]
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+cell bool
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+cell Is the word part of a "stop list"?
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+row
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+cell #[code pos]
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+cell int
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+cell Coarse-grained part-of-speech.
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+row
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+cell #[code pos_]
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+cell unicode
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+cell Coarse-grained part-of-speech.
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+row
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+cell #[code tag]
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+cell int
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+cell Fine-grained part-of-speech.
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+row
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+cell #[code tag_]
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+cell unicode
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+cell Fine-grained part-of-speech.
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+row
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+cell #[code dep]
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+cell int
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+cell Syntactic dependency relation.
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+row
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+cell #[code dep_]
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+cell unicode
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+cell Syntactic dependency relation.
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+row
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+cell #[code lang]
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+cell int
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+cell Language of the parent document's vocabulary.
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+row
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+cell #[code lang_]
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+cell unicode
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+cell Language of the parent document's vocabulary.
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+row
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+cell #[code prob]
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+cell float
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+cell Smoothed log probability estimate of token's type.
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+row
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+cell #[code idx]
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+cell int
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+cell The character offset of the token within the parent document.
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+row
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+cell #[code sentiment]
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+cell float
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+cell A scalar value indicating the positivity or negativity of the token.
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+row
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+cell #[code lex_id]
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+cell int
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+cell ID of the token's lexical type.
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