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spaCy/spacy/tokens/token.pyx
adrianeboyd 9be90dbca3
Improve token head verification (#5079) 
* Improve token head verification

Improve the verification for valid token heads when heads are set:

* in `Token.head`: heads come from the same document
* in `Doc.from_array()`: head indices are within the bounds of the
document

* Improve error message
2020-03-03 21:44:51 +01:00

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# cython: infer_types=True
# coding: utf8
from __future__ import unicode_literals
from libc.string cimport memcpy
from cpython.mem cimport PyMem_Malloc, PyMem_Free
# Compiler crashes on memory view coercion without this. Should report bug.
from cython.view cimport array as cvarray
cimport numpy as np
np.import_array()
import numpy
from thinc.neural.util import get_array_module
from ..typedefs cimport hash_t
from ..lexeme cimport Lexeme
from ..attrs cimport IS_ALPHA, IS_ASCII, IS_DIGIT, IS_LOWER, IS_PUNCT, IS_SPACE
from ..attrs cimport IS_BRACKET, IS_QUOTE, IS_LEFT_PUNCT, IS_RIGHT_PUNCT
from ..attrs cimport IS_OOV, IS_TITLE, IS_UPPER, IS_CURRENCY, LIKE_URL, LIKE_NUM, LIKE_EMAIL
from ..attrs cimport IS_STOP, ID, ORTH, NORM, LOWER, SHAPE, PREFIX, SUFFIX
from ..attrs cimport LENGTH, CLUSTER, LEMMA, POS, TAG, DEP
from ..symbols cimport conj
from .. import parts_of_speech
from .. import util
from ..compat import is_config
from ..errors import Errors, Warnings, user_warning, models_warning
from .underscore import Underscore, get_ext_args
from .morphanalysis cimport MorphAnalysis
cdef class Token:
"""An individual token – i.e. a word, punctuation symbol, whitespace,
etc.
DOCS: https://spacy.io/api/token
"""
@classmethod
def set_extension(cls, name, **kwargs):
"""Define a custom attribute which becomes available as `Token._`.
name (unicode): Name of the attribute to set.
default: Optional default value of the attribute.
getter (callable): Optional getter function.
setter (callable): Optional setter function.
method (callable): Optional method for method extension.
force (bool): Force overwriting existing attribute.
DOCS: https://spacy.io/api/token#set_extension
USAGE: https://spacy.io/usage/processing-pipelines#custom-components-attributes
"""
if cls.has_extension(name) and not kwargs.get("force", False):
raise ValueError(Errors.E090.format(name=name, obj="Token"))
Underscore.token_extensions[name] = get_ext_args(**kwargs)
@classmethod
def get_extension(cls, name):
"""Look up a previously registered extension by name.
name (unicode): Name of the extension.
RETURNS (tuple): A `(default, method, getter, setter)` tuple.
DOCS: https://spacy.io/api/token#get_extension
"""
return Underscore.token_extensions.get(name)
@classmethod
def has_extension(cls, name):
"""Check whether an extension has been registered.
name (unicode): Name of the extension.
RETURNS (bool): Whether the extension has been registered.
DOCS: https://spacy.io/api/token#has_extension
"""
return name in Underscore.token_extensions
@classmethod
def remove_extension(cls, name):
"""Remove a previously registered extension.
name (unicode): Name of the extension.
RETURNS (tuple): A `(default, method, getter, setter)` tuple of the
removed extension.
DOCS: https://spacy.io/api/token#remove_extension
"""
if not cls.has_extension(name):
raise ValueError(Errors.E046.format(name=name))
return Underscore.token_extensions.pop(name)
def __cinit__(self, Vocab vocab, Doc doc, int offset):
"""Construct a `Token` object.
vocab (Vocab): A storage container for lexical types.
doc (Doc): The parent document.
offset (int): The index of the token within the document.
DOCS: https://spacy.io/api/token#init
"""
self.vocab = vocab
self.doc = doc
self.c = &self.doc.c[offset]
self.i = offset
def __hash__(self):
return hash((self.doc, self.i))
def __len__(self):
"""The number of unicode characters in the token, i.e. `token.text`.
RETURNS (int): The number of unicode characters in the token.
DOCS: https://spacy.io/api/token#len
"""
return self.c.lex.length
def __unicode__(self):
return self.text
def __bytes__(self):
return self.text.encode('utf8')
def __str__(self):
if is_config(python3=True):
return self.__unicode__()
return self.__bytes__()
def __repr__(self):
return self.__str__()
def __richcmp__(self, Token other, int op):
# http://cython.readthedocs.io/en/latest/src/userguide/special_methods.html
if other is None:
if op in (0, 1, 2):
return False
else:
return True
cdef Doc my_doc = self.doc
cdef Doc other_doc = other.doc
my = self.idx
their = other.idx
if op == 0:
return my < their
elif op == 2:
if my_doc is other_doc:
return my == their
else:
return False
elif op == 4:
return my > their
elif op == 1:
return my <= their
elif op == 3:
if my_doc is other_doc:
return my != their
else:
return True
elif op == 5:
return my >= their
else:
raise ValueError(Errors.E041.format(op=op))
def __reduce__(self):
raise NotImplementedError(Errors.E111)
@property
def _(self):
"""Custom extension attributes registered via `set_extension`."""
return Underscore(Underscore.token_extensions, self,
start=self.idx, end=None)
cpdef bint check_flag(self, attr_id_t flag_id) except -1:
"""Check the value of a boolean flag.
flag_id (int): The ID of the flag attribute.
RETURNS (bool): Whether the flag is set.
DOCS: https://spacy.io/api/token#check_flag
"""
return Lexeme.c_check_flag(self.c.lex, flag_id)
def nbor(self, int i=1):
"""Get a neighboring token.
i (int): The relative position of the token to get. Defaults to 1.
RETURNS (Token): The token at position `self.doc[self.i+i]`.
DOCS: https://spacy.io/api/token#nbor
"""
if self.i+i < 0 or (self.i+i >= len(self.doc)):
raise IndexError(Errors.E042.format(i=self.i, j=i, length=len(self.doc)))
return self.doc[self.i+i]
def similarity(self, other):
"""Make a semantic similarity estimate. The default estimate is cosine
similarity using an average of word vectors.
other (object): The object to compare with. By default, accepts `Doc`,
`Span`, `Token` and `Lexeme` objects.
RETURNS (float): A scalar similarity score. Higher is more similar.
DOCS: https://spacy.io/api/token#similarity
"""
if "similarity" in self.doc.user_token_hooks:
return self.doc.user_token_hooks["similarity"](self, other)
if hasattr(other, "__len__") and len(other) == 1 and hasattr(other, "__getitem__"):
if self.c.lex.orth == getattr(other[0], "orth", None):
return 1.0
elif hasattr(other, "orth"):
if self.c.lex.orth == other.orth:
return 1.0
if self.vocab.vectors.n_keys == 0:
models_warning(Warnings.W007.format(obj="Token"))
if self.vector_norm == 0 or other.vector_norm == 0:
user_warning(Warnings.W008.format(obj="Token"))
return 0.0
vector = self.vector
xp = get_array_module(vector)
return (xp.dot(vector, other.vector) / (self.vector_norm * other.vector_norm))
@property
def morph(self):
return MorphAnalysis.from_id(self.vocab, self.c.morph)
@property
def lex_id(self):
"""RETURNS (int): Sequential ID of the token's lexical type."""
return self.c.lex.id
@property
def rank(self):
"""RETURNS (int): Sequential ID of the token's lexical type, used to
index into tables, e.g. for word vectors."""
return self.c.lex.id
@property
def string(self):
"""Deprecated: Use Token.text_with_ws instead."""
return self.text_with_ws
@property
def text(self):
"""RETURNS (unicode): The original verbatim text of the token."""
return self.orth_
@property
def text_with_ws(self):
"""RETURNS (unicode): The text content of the span (with trailing
whitespace).
"""
cdef unicode orth = self.vocab.strings[self.c.lex.orth]
if self.c.spacy:
return orth + " "
else:
return orth
@property
def prob(self):
"""RETURNS (float): Smoothed log probability estimate of token type."""
return self.c.lex.prob
@property
def sentiment(self):
"""RETURNS (float): A scalar value indicating the positivity or
negativity of the token."""
if "sentiment" in self.doc.user_token_hooks:
return self.doc.user_token_hooks["sentiment"](self)
return self.c.lex.sentiment
@property
def lang(self):
"""RETURNS (uint64): ID of the language of the parent document's
vocabulary.
"""
return self.c.lex.lang
@property
def idx(self):
"""RETURNS (int): The character offset of the token within the parent
document.
"""
return self.c.idx
@property
def cluster(self):
"""RETURNS (int): Brown cluster ID."""
return self.c.lex.cluster
@property
def orth(self):
"""RETURNS (uint64): ID of the verbatim text content."""
return self.c.lex.orth
@property
def lower(self):
"""RETURNS (uint64): ID of the lowercase token text."""
return self.c.lex.lower
@property
def norm(self):
"""RETURNS (uint64): ID of the token's norm, i.e. a normalised form of
the token text. Usually set in the language's tokenizer exceptions
or norm exceptions.
"""
if self.c.norm == 0:
return self.c.lex.norm
else:
return self.c.norm
@property
def shape(self):
"""RETURNS (uint64): ID of the token's shape, a transform of the
tokens's string, to show orthographic features (e.g. "Xxxx", "dd").
"""
return self.c.lex.shape
@property
def prefix(self):
"""RETURNS (uint64): ID of a length-N substring from the start of the
token. Defaults to `N=1`.
"""
return self.c.lex.prefix
@property
def suffix(self):
"""RETURNS (uint64): ID of a length-N substring from the end of the
token. Defaults to `N=3`.
"""
return self.c.lex.suffix
property lemma:
"""RETURNS (uint64): ID of the base form of the word, with no
inflectional suffixes.
"""
def __get__(self):
if self.c.lemma == 0:
lemma_ = self.vocab.morphology.lemmatizer.lookup(self.orth_, orth=self.orth)
return self.vocab.strings[lemma_]
else:
return self.c.lemma
def __set__(self, attr_t lemma):
self.c.lemma = lemma
property pos:
"""RETURNS (uint64): ID of coarse-grained part-of-speech tag."""
def __get__(self):
return self.c.pos
def __set__(self, pos):
self.c.pos = pos
property tag:
"""RETURNS (uint64): ID of fine-grained part-of-speech tag."""
def __get__(self):
return self.c.tag
def __set__(self, attr_t tag):
self.vocab.morphology.assign_tag(self.c, tag)
property dep:
"""RETURNS (uint64): ID of syntactic dependency label."""
def __get__(self):
return self.c.dep
def __set__(self, attr_t label):
self.c.dep = label
@property
def has_vector(self):
"""A boolean value indicating whether a word vector is associated with
the object.
RETURNS (bool): Whether a word vector is associated with the object.
DOCS: https://spacy.io/api/token#has_vector
"""
if "has_vector" in self.doc.user_token_hooks:
return self.doc.user_token_hooks["has_vector"](self)
if self.vocab.vectors.size == 0 and self.doc.tensor.size != 0:
return True
return self.vocab.has_vector(self.c.lex.orth)
@property
def vector(self):
"""A real-valued meaning representation.
RETURNS (numpy.ndarray[ndim=1, dtype='float32']): A 1D numpy array
representing the token's semantics.
DOCS: https://spacy.io/api/token#vector
"""
if "vector" in self.doc.user_token_hooks:
return self.doc.user_token_hooks["vector"](self)
if self.vocab.vectors.size == 0 and self.doc.tensor.size != 0:
return self.doc.tensor[self.i]
else:
return self.vocab.get_vector(self.c.lex.orth)
@property
def vector_norm(self):
"""The L2 norm of the token's vector representation.
RETURNS (float): The L2 norm of the vector representation.
DOCS: https://spacy.io/api/token#vector_norm
"""
if "vector_norm" in self.doc.user_token_hooks:
return self.doc.user_token_hooks["vector_norm"](self)
vector = self.vector
xp = get_array_module(vector)
total = (vector ** 2).sum()
return xp.sqrt(total) if total != 0. else 0.
@property
def tensor(self):
if self.doc.tensor is None:
return None
return self.doc.tensor[self.i]
@property
def n_lefts(self):
"""The number of leftward immediate children of the word, in the
syntactic dependency parse.
RETURNS (int): The number of leftward immediate children of the
word, in the syntactic dependency parse.
DOCS: https://spacy.io/api/token#n_lefts
"""
return self.c.l_kids
@property
def n_rights(self):
"""The number of rightward immediate children of the word, in the
syntactic dependency parse.
RETURNS (int): The number of rightward immediate children of the
word, in the syntactic dependency parse.
DOCS: https://spacy.io/api/token#n_rights
"""
return self.c.r_kids
@property
def sent(self):
"""RETURNS (Span): The sentence span that the token is a part of."""
if 'sent' in self.doc.user_token_hooks:
return self.doc.user_token_hooks["sent"](self)
return self.doc[self.i : self.i+1].sent
property sent_start:
def __get__(self):
"""Deprecated: use Token.is_sent_start instead."""
# Raising a deprecation warning here causes errors for autocomplete
# Handle broken backwards compatibility case: doc[0].sent_start
# was False.
if self.i == 0:
return False
else:
return self.c.sent_start
def __set__(self, value):
self.is_sent_start = value
property is_sent_start:
"""A boolean value indicating whether the token starts a sentence.
`None` if unknown. Defaults to `True` for the first token in the `Doc`.
RETURNS (bool / None): Whether the token starts a sentence.
None if unknown.
DOCS: https://spacy.io/api/token#is_sent_start
"""
def __get__(self):
if self.c.sent_start == 0:
return None
elif self.c.sent_start < 0:
return False
else:
return True
def __set__(self, value):
if self.doc.is_parsed:
raise ValueError(Errors.E043)
if value is None:
self.c.sent_start = 0
elif value is True:
self.c.sent_start = 1
elif value is False:
self.c.sent_start = -1
else:
raise ValueError(Errors.E044.format(value=value))
@property
def lefts(self):
"""The leftward immediate children of the word, in the syntactic
dependency parse.
YIELDS (Token): A left-child of the token.
DOCS: https://spacy.io/api/token#lefts
"""
cdef int nr_iter = 0
cdef const TokenC* ptr = self.c - (self.i - self.c.l_edge)
while ptr < self.c:
if ptr + ptr.head == self.c:
yield self.doc[ptr - (self.c - self.i)]
ptr += 1
nr_iter += 1
# This is ugly, but it's a way to guard out infinite loops
if nr_iter >= 10000000:
raise RuntimeError(Errors.E045.format(attr="token.lefts"))
@property
def rights(self):
"""The rightward immediate children of the word, in the syntactic
dependency parse.
YIELDS (Token): A right-child of the token.
DOCS: https://spacy.io/api/token#rights
"""
cdef const TokenC* ptr = self.c + (self.c.r_edge - self.i)
tokens = []
cdef int nr_iter = 0
while ptr > self.c:
if ptr + ptr.head == self.c:
tokens.append(self.doc[ptr - (self.c - self.i)])
ptr -= 1
nr_iter += 1
if nr_iter >= 10000000:
raise RuntimeError(Errors.E045.format(attr="token.rights"))
tokens.reverse()
for t in tokens:
yield t
@property
def children(self):
"""A sequence of the token's immediate syntactic children.
YIELDS (Token): A child token such that `child.head==self`.
DOCS: https://spacy.io/api/token#children
"""
yield from self.lefts
yield from self.rights
@property
def subtree(self):
"""A sequence containing the token and all the token's syntactic
descendants.
YIELDS (Token): A descendent token such that
`self.is_ancestor(descendent) or token == self`.
DOCS: https://spacy.io/api/token#subtree
"""
for word in self.lefts:
yield from word.subtree
yield self
for word in self.rights:
yield from word.subtree
@property
def left_edge(self):
"""The leftmost token of this token's syntactic descendents.
RETURNS (Token): The first token such that `self.is_ancestor(token)`.
"""
return self.doc[self.c.l_edge]
@property
def right_edge(self):
"""The rightmost token of this token's syntactic descendents.
RETURNS (Token): The last token such that `self.is_ancestor(token)`.
"""
return self.doc[self.c.r_edge]
@property
def ancestors(self):
"""A sequence of this token's syntactic ancestors.
YIELDS (Token): A sequence of ancestor tokens such that
`ancestor.is_ancestor(self)`.
DOCS: https://spacy.io/api/token#ancestors
"""
cdef const TokenC* head_ptr = self.c
# Guard against infinite loop, no token can have
# more ancestors than tokens in the tree.
cdef int i = 0
while head_ptr.head != 0 and i < self.doc.length:
head_ptr += head_ptr.head
yield self.doc[head_ptr - (self.c - self.i)]
i += 1
def is_ancestor(self, descendant):
"""Check whether this token is a parent, grandparent, etc. of another
in the dependency tree.
descendant (Token): Another token.
RETURNS (bool): Whether this token is the ancestor of the descendant.
DOCS: https://spacy.io/api/token#is_ancestor
"""
if self.doc is not descendant.doc:
return False
return any(ancestor.i == self.i for ancestor in descendant.ancestors)
property head:
"""The syntactic parent, or "governor", of this token.
RETURNS (Token): The token predicted by the parser to be the head of
the current token.
"""
def __get__(self):
return self.doc[self.i + self.c.head]
def __set__(self, Token new_head):
# This function sets the head of self to new_head and updates the
# counters for left/right dependents and left/right corner for the
# new and the old head
# Check that token is from the same document
if self.doc != new_head.doc:
raise ValueError(Errors.E191)
# Do nothing if old head is new head
if self.i + self.c.head == new_head.i:
return
cdef Token old_head = self.head
cdef int rel_newhead_i = new_head.i - self.i
# Is the new head a descendant of the old head
cdef bint is_desc = old_head.is_ancestor(new_head)
cdef int new_edge
cdef Token anc, child
# Update number of deps of old head
if self.c.head > 0: # left dependent
old_head.c.l_kids -= 1
if self.c.l_edge == old_head.c.l_edge:
# The token dominates the left edge so the left edge of
# the head may change when the token is reattached, it may
# not change if the new head is a descendant of the current
# head.
new_edge = self.c.l_edge
# The new l_edge is the left-most l_edge on any of the
# other dependents where the l_edge is left of the head,
# otherwise it is the head
if not is_desc:
new_edge = old_head.i
for child in old_head.children:
if child == self:
continue
if child.c.l_edge < new_edge:
new_edge = child.c.l_edge
old_head.c.l_edge = new_edge
# Walk up the tree from old_head and assign new l_edge to
# ancestors until an ancestor already has an l_edge that's
# further left
for anc in old_head.ancestors:
if anc.c.l_edge <= new_edge:
break
anc.c.l_edge = new_edge
elif self.c.head < 0: # right dependent
old_head.c.r_kids -= 1
# Do the same thing as for l_edge
if self.c.r_edge == old_head.c.r_edge:
new_edge = self.c.r_edge
if not is_desc:
new_edge = old_head.i
for child in old_head.children:
if child == self:
continue
if child.c.r_edge > new_edge:
new_edge = child.c.r_edge
old_head.c.r_edge = new_edge
for anc in old_head.ancestors:
if anc.c.r_edge >= new_edge:
break
anc.c.r_edge = new_edge
# Update number of deps of new head
if rel_newhead_i > 0: # left dependent
new_head.c.l_kids += 1
# Walk up the tree from new head and set l_edge to self.l_edge
# until you hit a token with an l_edge further to the left
if self.c.l_edge < new_head.c.l_edge:
new_head.c.l_edge = self.c.l_edge
for anc in new_head.ancestors:
if anc.c.l_edge <= self.c.l_edge:
break
anc.c.l_edge = self.c.l_edge
elif rel_newhead_i < 0: # right dependent
new_head.c.r_kids += 1
# Do the same as for l_edge
if self.c.r_edge > new_head.c.r_edge:
new_head.c.r_edge = self.c.r_edge
for anc in new_head.ancestors:
if anc.c.r_edge >= self.c.r_edge:
break
anc.c.r_edge = self.c.r_edge
# Set new head
self.c.head = rel_newhead_i
@property
def conjuncts(self):
"""A sequence of coordinated tokens, including the token itself.
RETURNS (tuple): The coordinated tokens.
DOCS: https://spacy.io/api/token#conjuncts
"""
cdef Token word, child
if "conjuncts" in self.doc.user_token_hooks:
return tuple(self.doc.user_token_hooks["conjuncts"](self))
start = self
while start.i != start.head.i:
if start.dep == conj:
start = start.head
else:
break
queue = [start]
output = [start]
for word in queue:
for child in word.rights:
if child.c.dep == conj:
output.append(child)
queue.append(child)
return tuple([w for w in output if w.i != self.i])
property ent_type:
"""RETURNS (uint64): Named entity type."""
def __get__(self):
return self.c.ent_type
def __set__(self, ent_type):
self.c.ent_type = ent_type
property ent_type_:
"""RETURNS (unicode): Named entity type."""
def __get__(self):
return self.vocab.strings[self.c.ent_type]
def __set__(self, ent_type):
self.c.ent_type = self.vocab.strings.add(ent_type)
@property
def ent_iob(self):
"""IOB code of named entity tag. `1="I", 2="O", 3="B"`. 0 means no tag
is assigned.
RETURNS (uint64): IOB code of named entity tag.
"""
return self.c.ent_iob
@property
def ent_iob_(self):
"""IOB code of named entity tag. "B" means the token begins an entity,
"I" means it is inside an entity, "O" means it is outside an entity,
and "" means no entity tag is set. "B" with an empty ent_type
means that the token is blocked from further processing by NER.
RETURNS (unicode): IOB code of named entity tag.
"""
iob_strings = ("", "I", "O", "B")
return iob_strings[self.c.ent_iob]
property ent_id:
"""RETURNS (uint64): ID of the entity the token is an instance of,
if any.
"""
def __get__(self):
return self.c.ent_id
def __set__(self, hash_t key):
self.c.ent_id = key
property ent_id_:
"""RETURNS (unicode): ID of the entity the token is an instance of,
if any.
"""
def __get__(self):
return self.vocab.strings[self.c.ent_id]
def __set__(self, name):
self.c.ent_id = self.vocab.strings.add(name)
property ent_kb_id:
"""RETURNS (uint64): Named entity KB ID."""
def __get__(self):
return self.c.ent_kb_id
def __set__(self, attr_t ent_kb_id):
self.c.ent_kb_id = ent_kb_id
property ent_kb_id_:
"""RETURNS (unicode): Named entity KB ID."""
def __get__(self):
return self.vocab.strings[self.c.ent_kb_id]
def __set__(self, ent_kb_id):
self.c.ent_kb_id = self.vocab.strings.add(ent_kb_id)
@property
def whitespace_(self):
"""RETURNS (unicode): The trailing whitespace character, if present."""
return " " if self.c.spacy else ""
@property
def orth_(self):
"""RETURNS (unicode): Verbatim text content (identical to
`Token.text`). Exists mostly for consistency with the other
attributes.
"""
return self.vocab.strings[self.c.lex.orth]
@property
def lower_(self):
"""RETURNS (unicode): The lowercase token text. Equivalent to
`Token.text.lower()`.
"""
return self.vocab.strings[self.c.lex.lower]
property norm_:
"""RETURNS (unicode): The token's norm, i.e. a normalised form of the
token text. Usually set in the language's tokenizer exceptions or
norm exceptions.
"""
def __get__(self):
return self.vocab.strings[self.norm]
def __set__(self, unicode norm_):
self.c.norm = self.vocab.strings.add(norm_)
@property
def shape_(self):
"""RETURNS (unicode): Transform of the tokens's string, to show
orthographic features. For example, "Xxxx" or "dd".
"""
return self.vocab.strings[self.c.lex.shape]
@property
def prefix_(self):
"""RETURNS (unicode): A length-N substring from the start of the token.
Defaults to `N=1`.
"""
return self.vocab.strings[self.c.lex.prefix]
@property
def suffix_(self):
"""RETURNS (unicode): A length-N substring from the end of the token.
Defaults to `N=3`.
"""
return self.vocab.strings[self.c.lex.suffix]
@property
def lang_(self):
"""RETURNS (unicode): Language of the parent document's vocabulary,
e.g. 'en'.
"""
return self.vocab.strings[self.c.lex.lang]
property lemma_:
"""RETURNS (unicode): The token lemma, i.e. the base form of the word,
with no inflectional suffixes.
"""
def __get__(self):
if self.c.lemma == 0:
return self.vocab.morphology.lemmatizer.lookup(self.orth_, orth=self.orth)
else:
return self.vocab.strings[self.c.lemma]
def __set__(self, unicode lemma_):
self.c.lemma = self.vocab.strings.add(lemma_)
property pos_:
"""RETURNS (unicode): Coarse-grained part-of-speech tag."""
def __get__(self):
return parts_of_speech.NAMES[self.c.pos]
def __set__(self, pos_name):
self.c.pos = parts_of_speech.IDS[pos_name]
property tag_:
"""RETURNS (unicode): Fine-grained part-of-speech tag."""
def __get__(self):
return self.vocab.strings[self.c.tag]
def __set__(self, tag):
self.tag = self.vocab.strings.add(tag)
property dep_:
"""RETURNS (unicode): The syntactic dependency label."""
def __get__(self):
return self.vocab.strings[self.c.dep]
def __set__(self, unicode label):
self.c.dep = self.vocab.strings.add(label)
@property
def is_oov(self):
"""RETURNS (bool): Whether the token is out-of-vocabulary."""
return Lexeme.c_check_flag(self.c.lex, IS_OOV)
@property
def is_stop(self):
"""RETURNS (bool): Whether the token is a stop word, i.e. part of a
"stop list" defined by the language data.
"""
return Lexeme.c_check_flag(self.c.lex, IS_STOP)
@property
def is_alpha(self):
"""RETURNS (bool): Whether the token consists of alpha characters.
Equivalent to `token.text.isalpha()`.
"""
return Lexeme.c_check_flag(self.c.lex, IS_ALPHA)
@property
def is_ascii(self):
"""RETURNS (bool): Whether the token consists of ASCII characters.
Equivalent to `[any(ord(c) >= 128 for c in token.text)]`.
"""
return Lexeme.c_check_flag(self.c.lex, IS_ASCII)
@property
def is_digit(self):
"""RETURNS (bool): Whether the token consists of digits. Equivalent to
`token.text.isdigit()`.
"""
return Lexeme.c_check_flag(self.c.lex, IS_DIGIT)
@property
def is_lower(self):
"""RETURNS (bool): Whether the token is in lowercase. Equivalent to
`token.text.islower()`.
"""
return Lexeme.c_check_flag(self.c.lex, IS_LOWER)
@property
def is_upper(self):
"""RETURNS (bool): Whether the token is in uppercase. Equivalent to
`token.text.isupper()`
"""
return Lexeme.c_check_flag(self.c.lex, IS_UPPER)
@property
def is_title(self):
"""RETURNS (bool): Whether the token is in titlecase. Equivalent to
`token.text.istitle()`.
"""
return Lexeme.c_check_flag(self.c.lex, IS_TITLE)
@property
def is_punct(self):
"""RETURNS (bool): Whether the token is punctuation."""
return Lexeme.c_check_flag(self.c.lex, IS_PUNCT)
@property
def is_space(self):
"""RETURNS (bool): Whether the token consists of whitespace characters.
Equivalent to `token.text.isspace()`.
"""
return Lexeme.c_check_flag(self.c.lex, IS_SPACE)
@property
def is_bracket(self):
"""RETURNS (bool): Whether the token is a bracket."""
return Lexeme.c_check_flag(self.c.lex, IS_BRACKET)
@property
def is_quote(self):
"""RETURNS (bool): Whether the token is a quotation mark."""
return Lexeme.c_check_flag(self.c.lex, IS_QUOTE)
@property
def is_left_punct(self):
"""RETURNS (bool): Whether the token is a left punctuation mark."""
return Lexeme.c_check_flag(self.c.lex, IS_LEFT_PUNCT)
@property
def is_right_punct(self):
"""RETURNS (bool): Whether the token is a right punctuation mark."""
return Lexeme.c_check_flag(self.c.lex, IS_RIGHT_PUNCT)
@property
def is_currency(self):
"""RETURNS (bool): Whether the token is a currency symbol."""
return Lexeme.c_check_flag(self.c.lex, IS_CURRENCY)
@property
def like_url(self):
"""RETURNS (bool): Whether the token resembles a URL."""
return Lexeme.c_check_flag(self.c.lex, LIKE_URL)
@property
def like_num(self):
"""RETURNS (bool): Whether the token resembles a number, e.g. "10.9",
"10", "ten", etc.
"""
return Lexeme.c_check_flag(self.c.lex, LIKE_NUM)
@property
def like_email(self):
"""RETURNS (bool): Whether the token resembles an email address."""
return Lexeme.c_check_flag(self.c.lex, LIKE_EMAIL)
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