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* Refactoring with Lexeme as a class now compiles. Basic design seems to work

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This commit is contained in:
Matthew Honnibal 2014-08-27 17:15:39 +02:00
parent 68bae2fec6
commit e9a62b6eba
7 changed files with 196 additions and 484 deletions
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14
spacy/en.pxd
View File

@ -1,4 +1,4 @@
from spacy.spacy cimport Language
from spacy.lang cimport Language
from spacy.word cimport Lexeme
cimport cython
@ -31,12 +31,14 @@ cpdef size_t POS
cpdef size_t PRON
cpdef size_t PRT
cdef class English(spacy.Language):
cdef int find_split(self, unicode word)
cpdef size_t SIC
cpdef size_t CANON_CASED
cpdef size_t SHAPE
cpdef size_t NON_SPARSE
cdef English EN
cdef class English(Language):
cpdef int _split_one(self, unicode word)
cpdef Word lookup(unicode word)
cpdef list tokenize(unicode string)
cpdef English EN

189
spacy/en.pyx
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@ -31,6 +31,7 @@ same scheme. Tokenization problems are a major cause of poor performance for
NLP tools. If you're using a pre-trained model, the :py:mod:`spacy.ptb3` module
provides a fully Penn Treebank 3-compliant tokenizer.
'''
# TODO
#The script translate_treebank_tokenization can be used to transform a treebank's
#annotation to use one of the spacy tokenization schemes.
@ -40,90 +41,14 @@ from __future__ import unicode_literals
from libc.stdlib cimport malloc, calloc, free
from libc.stdint cimport uint64_t
cimport spacy
cimport lang
# Python-readable flag constants --- can't read an enum from Python
# Don't want to manually assign these numbers, or we'll insert one and have to
# change them all.
# Don't use "i", as we don't want it in the global scope!
cdef size_t __i = 0
ALPHA = __i; i += 1
DIGIT = __i; __i += 1
PUNCT = __i; __i += 1
SPACE = __i; __i += 1
LOWER = __i; __i += 1
UPPER = __i; __i += 1
TITLE = __i; __i += 1
ASCII = __i; __i += 1
OFT_LOWER = __i; __i += 1
OFT_UPPER = __i; __i += 1
OFT_TITLE = __i; __i += 1
PUNCT = __i; __i += 1
CONJ = __i; __i += 1
NUM = __i; __i += 1
X = __i; __i += 1
DET = __i; __i += 1
ADP = __i; __i += 1
ADJ = __i; __i += 1
ADV = __i; __i += 1
VERB = __i; __i += 1
NOUN = __i; __i += 1
PDT = __i; __i += 1
POS = __i; __i += 1
PRON = __i; __i += 1
PRT = __i; __i += 1
# These are for the string views
__i = 0
SIC = __i; __i += 1
CANON_CASED = __i; __i += 1
NON_SPARSE = __i; __i += 1
SHAPE = __i; __i += 1
NR_STRING_VIEWS = __i
def get_string_views(unicode string, lexeme):
views = ['' for _ in range(NR_STRING_VIEWS)]
views[SIC] = string
views[CANON_CASED] = canonicalize_case(string, lexeme)
views[SHAPE] = get_string_shape(string)
views[NON_SPARSE] = get_non_sparse(string, views[CANON_CASED], views[SHAPE],
lexeme)
return views
def set_orth_flags(unicode string, flags_t flags)
setters = [
(ALPHA, is_alpha),
(DIGIT, is_digit),
(PUNCT, is_punct),
(SPACE, is_space),
(LOWER, is_lower),
(UPPER, is_upper),
(SPACE, is_space)
]
for bit, setter in setters:
if setter(string):
flags |= 1 << bit
return flags
from spacy import orth
cdef class English(spacy.Language):
cdef Lexeme new_lexeme(self, unicode string, cluster=0, prob=0, case_stats=None,
tag_freqs=None):
return Lexeme(s, length, views, prob=prob, cluster=cluster,
flags=self.get_flags(string))
cdef int find_split(self, unicode word):
cdef class English(Language):
cpdef int _split_one(self, unicode word):
cdef size_t length = len(word)
cdef int i = 0
if word.startswith("'s") or word.startswith("'S"):
@ -132,17 +57,16 @@ cdef class English(spacy.Language):
if word.endswith("'s") and length >= 3:
return length - 2
# Leading punctuation
if check_punct(word, 0, length):
if _check_punct(word, 0, length):
return 1
elif length >= 1:
# Split off all trailing punctuation characters
i = 0
while i < length and not check_punct(word, i, length):
while i < length and not _check_punct(word, i, length):
i += 1
return i
cdef bint check_punct(unicode word, size_t i, size_t length):
cdef bint _check_punct(unicode word, size_t i, size_t length):
# Don't count appostrophes as punct if the next char is a letter
if word[i] == "'" and i < (length - 1) and word[i+1].isalpha():
return i == 0
@ -160,69 +84,46 @@ cdef bint check_punct(unicode word, size_t i, size_t length):
EN = English('en')
cpdef list tokenize(unicode string):
"""Tokenize a string.
The tokenization rules are defined in two places:
* The data/en/tokenization table, which handles special cases like contractions;
* The :py:meth:`spacy.en.English.find_split` function, which is used to split off punctuation etc.
Args:
string (unicode): The string to be tokenized.
Returns:
tokens (Tokens): A Tokens object, giving access to a sequence of LexIDs.
"""
return EN.tokenize(string)
# Thresholds for frequency related flags
TAG_THRESH = 0.5
LOWER_THRESH = 0.5
UPPER_THRESH = 0.3
TITLE_THRESH = 0.9
cpdef Lexeme lookup(unicode string):
"""Retrieve (or create, if not found) a Lexeme for a string, and return its ID.
# Python-readable flag constants --- can't read an enum from Python
ALPHA = EN.lexicon.add_flag(orth.is_alpha)
DIGIT = EN.lexicon.add_flag(orth.is_digit)
PUNCT = EN.lexicon.add_flag(orth.is_punct)
SPACE = EN.lexicon.add_flag(orth.is_space)
PUNCT = EN.lexicon.add_flag(orth.is_punct)
ASCII = EN.lexicon.add_flag(orth.is_ascii)
TITLE = EN.lexicon.add_flag(orth.is_title)
LOWER = EN.lexicon.add_flag(orth.is_lower)
UPPER = EN.lexicon.add_flag(orth.is_upper)
Properties of the Lexeme are accessed by passing LexID to the accessor methods.
Access is cheap/free, as the LexID is the memory address of the Lexeme.
OFT_LOWER = EN.lexicon.add_flag(orth.case_trend('lower', LOWER_THRESH))
OFT_UPPER = EN.lexicon.add_flag(orth.case_trend('upper', UPPER_THRESH))
OFT_TITLE = EN.lexicon.add_flag(orth.case_trend('title', TITLE_THRESH))
Args:
string (unicode): The string to be looked up. Must be unicode, not bytes.
Returns:
lexeme (LexID): A reference to a lexical type.
"""
return EN.lookup(string)
CAN_PUNCT = EN.lexicon.add_flag(orth.can_tag("PUNCT", TAG_THRESH))
CAN_CONJ = EN.lexicon.add_flag(orth.can_tag("CONJ", TAG_THRESH))
CAN_NUM = EN.lexicon.add_flag(orth.can_tag("NUM", TAG_THRESH))
CAN_N = EN.lexicon.add_flag(orth.can_tag("N", TAG_THRESH))
CAN_DET = EN.lexicon.add_flag(orth.can_tag("DET", TAG_THRESH))
CAN_ADP = EN.lexicon.add_flag(orth.can_tag("ADP", TAG_THRESH))
CAN_ADJ = EN.lexicon.add_flag(orth.can_tag("ADJ", TAG_THRESH))
CAN_ADV = EN.lexicon.add_flag(orth.can_tag("ADV", TAG_THRESH))
CAN_VERB = EN.lexicon.add_flag(orth.can_tag("VERB", TAG_THRESH))
CAN_NOUN = EN.lexicon.add_flag(orth.can_tag("NOUN", TAG_THRESH))
CAN_PDT = EN.lexicon.add_flag(orth.can_tag("PDT", TAG_THRESH))
CAN_POS = EN.lexicon.add_flag(orth.can_tag("POS", TAG_THRESH))
CAN_PRON = EN.lexicon.add_flag(orth.can_tag("PRON", TAG_THRESH))
CAN_PRT = EN.lexicon.add_flag(orth.can_tag("PRT", TAG_THRESH))
def add_string_views(view_funcs):
"""Add a string view to existing and previous lexical entries.
Args:
get_view (function): A unicode --> unicode function.
Returns:
view_id (int): An integer key you can use to access the view.
"""
pass
def load_clusters(location):
"""Load cluster data.
"""
pass
def load_unigram_probs(location):
"""Load unigram probabilities.
"""
pass
def load_case_stats(location):
"""Load case stats.
"""
pass
def load_tag_stats(location):
"""Load tag statistics.
"""
pass
# These are the name of string transforms
SIC = EN.lexicon.add_transform(orth.sic_string)
CANON_CASED = EN.lexicon.add_transform(orth.canon_case)
SHAPE = EN.lexicon.add_transform(orth.word_shape)
NON_SPARSE = EN.lexicon.add_transform(orth.non_sparse)

23
spacy/lang.pxd
View File

@ -3,18 +3,23 @@ from libc.stdint cimport uint64_t
from spacy.word cimport Lexeme
cdef class Lexicon:
cdef public list flag_checkers
cdef public list string_transformers
cdef dict lexicon
cpdef Lexeme lookup(self, unicode string)
cdef class Language:
cdef object name
cdef dict blobs
cdef dict lexicon
cdef dict cache
cpdef readonly Lexicon lexicon
cpdef list tokenize(self, unicode text)
cdef Word lookup(self, unicode string)
cdef list lookup_chunk(self, unicode chunk)
cdef list _tokenize(self, unicode string)
cpdef list _split(self, unicode string)
cpdef int _split_one(self, unicode word)
cdef list new_chunk(self, unicode string, list substrings)
cdef Word new_lexeme(self, unicode lex)
cpdef list find_substrings(self, unicode chunk)
cdef int find_split(self, unicode word)

206
spacy/lang.pyx
View File

@ -6,37 +6,37 @@ Provides the main implementation for the spacy tokenizer. Specific languages
subclass the Language class, over-writing the tokenization rules as necessary.
Special-case tokenization rules are read from data/<lang>/tokenization .
"""
from __future__ import unicode_literals
from libc.stdlib cimport calloc, free
from . import util
import json
from os import path
cdef class Language:
view_funcs = []
def __cinit__(self, name):
self.name = name
self.blobs = {}
self.lexicon = {}
self.cache = {}
self.lexicon = Lexicon()
self.load_tokenization(util.read_tokenization(name))
self.load_dist_info(util.read_dist_info(name))
cpdef list tokenize(self, unicode string):
"""Tokenize.
"""Tokenize a string.
Split the string into tokens.
The tokenization rules are defined in two places:
* The data/<lang>/tokenization table, which handles special cases like contractions;
* The appropriate :py:meth:`find_split` function, which is used to split
off punctuation etc.
Args:
string (unicode): The string to split.
string (unicode): The string to be tokenized.
Returns:
tokens (list): A list of Lexeme objects.
tokens (Tokens): A Tokens object, giving access to a sequence of LexIDs.
"""
cdef list blob
cdef list tokens = []
cdef size_t length = len(string)
cdef size_t start = 0
@ -44,74 +44,28 @@ cdef class Language:
for c in string:
if c == ' ':
if start < i:
blob = self.lookup_blob(string[start:i])
tokens.extend(blob)
tokens.extend(self._tokenize(string[start:i]))
start = i + 1
i += 1
if start < i:
chunk = self.lookup_blob(string[start:])
tokens.extend(chunk)
tokens.extend(self._tokenize(string[start:]))
return tokens
cdef Lexeme lookup(self, unicode string):
assert len(string) != 0
cdef Word word
if string in self.vocab:
word = self.vocab[string]
else:
word = self.new_lexeme(string)
return word
cdef list lookup_blob(self, unicode string):
cdef list chunk
cdef size_t blob_id
if string in self.blobs:
blob = self.blobs[string]
else:
blob = self.new_blob(string, self.find_substrings(string))
return chunk
cdef list new_blob(self, unicode string, list substrings):
blob = []
cdef list _tokenize(self, unicode string):
if string in self.cache:
return self.cache[string]
cdef list lexemes = []
substrings = self._split(string)
for i, substring in enumerate(substrings):
blob.append(self.lookup(substring))
self.blobs[string] = chunk
return blob
lexemes.append(self.lookup(substring))
self.cache[string] = lexemes
return lexemes
cdef Word new_lexeme(self, unicode string):
# TODO
#lexeme = Lexeme(string.encode('utf8'), string_views)
#return lexeme
"""
def add_view_funcs(self, list view_funcs):
self.view_funcs.extend(view_funcs)
cdef size_t nr_views = len(self.view_funcs)
cdef unicode view
cdef StringHash hashed
cdef StringHash key
cdef unicode string
cdef LexID lex_id
cdef Lexeme* word
for key, lex_id in self.vocab.items():
word = <Lexeme*>lex_id
free(word.string_views)
word.string_views = <StringHash*>calloc(nr_views, sizeof(StringHash))
string = word.string[:word.length].decode('utf8')
for i, view_func in enumerate(self.view_funcs):
view = view_func(string)
hashed = hash(view)
word.string_views[i] = hashed
self.bacov[hashed] = view
"""
cpdef list find_substrings(self, unicode blob):
"""Find how to split a chunk into substrings.
cpdef list _split(self, unicode string):
"""Find how to split a contiguous span of non-space characters into substrings.
This method calls find_split repeatedly. Most languages will want to
override find_split, but it may be useful to override this instead.
override _split_one, but it may be useful to override this instead.
Args:
chunk (unicode): The string to be split, e.g. u"Mike's!"
@ -120,22 +74,22 @@ cdef class Language:
substrings (list): The component substrings, e.g. [u"Mike", "'s", "!"].
"""
substrings = []
while blob:
split = self.find_split(blob)
while string:
split = self._split_one(string)
if split == 0:
substrings.append(blob)
substrings.append(string)
break
substrings.append(blob[:split])
blob = blob[split:]
substrings.append(string[:split])
string = string[split:]
return substrings
cdef int find_split(self, unicode word):
cpdef int _split_one(self, unicode word):
return len(word)
def load_tokenization(self, token_rules):
def load_special_tokenization(self, token_rules):
'''Load special-case tokenization rules.
Loads special-case tokenization rules into the Language.chunk cache,
Loads special-case tokenization rules into the Language.cache cache,
read from data/<lang>/tokenization . The special cases are loaded before
any language data is tokenized, giving these priority. For instance,
the English tokenization rules map "ain't" to ["are", "not"].
@ -144,25 +98,83 @@ cdef class Language:
token_rules (list): A list of (chunk, tokens) pairs, where chunk is
a string and tokens is a list of strings.
'''
for chunk, tokens in token_rules:
self.new_chunk(chunk, tokens)
for string, substrings in token_rules:
lexemes = []
for i, substring in enumerate(substrings):
lexemes.append(self.lookup(substring))
self.cache[string] = lexemes
def load_dist_info(self, dist_info):
'''Load distributional information for the known lexemes of the language.
The distributional information is read from data/<lang>/dist_info.json .
It contains information like the (smoothed) unigram log probability of
the word, how often the word is found upper-cased, how often the word
is found title-cased, etc.
'''
cdef class Lexicon:
def __cinit__(self):
self.flag_checkers = []
self.string_transforms = []
self.lexicon = {}
cpdef Lexeme lookup(self, unicode string):
"""Retrieve (or create, if not found) a Lexeme for a string, and return it.
Args:
string (unicode): The string to be looked up. Must be unicode, not bytes.
Returns:
lexeme (Lexeme): A reference to a lexical type.
"""
assert len(string) != 0
if string in self.lexicon:
return self.lexicon[string]
prob = _pop_default(self.probs, string, 0.0)
cluster = _pop_default(self.clusters, string, 0.0)
case_stats = _pop_default(self.case_stats, string, {})
tag_stats = _pop_default(self.tag_stats, string, {})
cdef Lexeme word = Lexeme(string, prob, cluster, case_stats, tag_stats,
self.flag_checkers, self.string_transformers)
self.lexicon[string] = word
return word
def add_flag(self, flag_checker):
cdef unicode string
cdef dict word_dist
cdef Word w
for string, word_dist in dist_info.items():
w = self.lookup(string)
w.prob = word_dist.prob
w.cluster = word_dist.cluster
for flag in word_dist.flags:
w.dist_flags |= DIST_FLAGS[flag]
for tag in word_dist.tagdict:
w.possible_tags |= TAGS[tag]
cdef Lexeme word
flag_id = len(self.flag_checkers)
for string, word in self.lexicon.items():
if flag_checker(string, word.prob, {}):
word.set_flag(flag_id)
self.flag_checkers.append(flag_checker)
return flag_id
def add_transform(self, string_transform):
self.string_transformers.append(string_transform)
return len(self.string_transformers) - 1
def load_probs(self, location):
"""Load unigram probabilities.
"""
self.probs = json.load(location)
cdef Lexeme word
cdef unicode string
for string, word in self.lexicon.items():
prob = _pop_default(self.probs, string, 0.0)
word.prob = prob
def load_clusters(self, location):
self.probs = json.load(location)
cdef Lexeme word
cdef unicode string
for string, word in self.lexicon.items():
cluster = _pop_default(self.cluster, string, 0)
word.cluster = cluster
def load_stats(self, location):
"""Load distributional stats.
"""
raise NotImplementedError
def _pop_default(dict d, key, default):
return d.pop(key) if key in d else default

54
spacy/util.py
View File

@ -1,54 +0,0 @@
import os
from os import path
import codecs
import json
DATA_DIR = path.join(path.dirname(__file__), '..', 'data')
def utf8open(loc, mode='r'):
return codecs.open(loc, mode, 'utf8')
def load_case_stats(data_dir):
case_loc = path.join(data_dir, 'case')
case_stats = {}
with utf8open(case_loc) as cases_file:
for line in cases_file:
word, upper, title = line.split()
case_stats[word] = (float(upper), float(title))
return case_stats
def read_dist_info(lang):
dist_path = path.join(DATA_DIR, lang, 'distribution_info.json')
if path.exists(dist_path):
with open(dist_path) as file_:
dist_info = json.load(file_)
else:
dist_info = {}
return dist_info
def read_tokenization(lang):
loc = path.join(DATA_DIR, lang, 'tokenization')
entries = []
seen = set()
with utf8open(loc) as file_:
for line in file_:
line = line.strip()
if line.startswith('#'):
continue
if not line:
continue
pieces = line.split()
chunk = pieces.pop(0)
assert chunk not in seen, chunk
seen.add(chunk)
entries.append((chunk, list(pieces)))
if chunk[0].isalpha() and chunk[0].islower():
chunk = chunk[0].title() + chunk[1:]
pieces[0] = pieces[0][0].title() + pieces[0][1:]
seen.add(chunk)
entries.append((chunk, pieces))
return entries

18
spacy/word.pxd
View File

@ -7,19 +7,19 @@ DEF MAX_FLAG = 64
cdef class Lexeme:
# NB: the readonly keyword refers to _Python_ access. The attributes are
# writeable from Cython.
cdef readonly id_t id
cdef readonly size_t length
cdef readonly double prob
cdef readonly size_t cluster
cpdef readonly id_t id
cpdef readonly size_t length
cpdef readonly double prob
cpdef readonly size_t cluster
cdef readonly utf8_t* strings
cdef readonly size_t nr_strings
cdef utf8_t* views
cdef size_t nr_views
cdef readonly flag_t flags
cpdef bint check_flag(self, size_t flag_id) except *
cpdef int set_flag(self, size_t flag_id) except -1
cpdef unicode get_string(self, size_t i) except *
cpdef id_t get_id(self, size_t i) except 0
cpdef int add_strings(self, list strings) except -1
cpdef unicode get_view_string(self, size_t i)
cpdef id_t get_view_id(self, size_t i) except 0
cpdef int add_view(self, unicode view) except -1

176
spacy/word.pyx
View File

@ -2,10 +2,7 @@
# cython: embedsignature=True
from libc.stdlib cimport calloc, free
from spacy cimport flags
from libc.stdlib cimport calloc, free, realloc
cdef class Lexeme:
"""A lexical type.
@ -53,7 +50,7 @@ cdef class Lexeme:
the same cluster ID as "pineapple", which is not what we'd like.
"""
def __cinit__(self, utf8_t string, size_t length, list views, prob=0.0,
cluster=0, orth_flags=0, dist_flags=0, possible_tags=0):
flags=0):
self.id = <id_t>&string
self.length = length
self.nr_strings = 0
@ -66,25 +63,21 @@ cdef class Lexeme:
def __get__(self):
return self.strings[0].decode('utf8')
cpdef unicode get_view_string(self, size_t i) except *:
cpdef unicode get_view_string(self, size_t i):
assert i < self.nr_strings
return self.strings[i].decode('utf8')
cpdef intptr_t get_view_id(self, size_t i) except 0:
cpdef id_t get_view_id(self, size_t i) except 0:
assert i < self.nr_strings
return <string_id_t>&self.views[i]
return <id_t>&self.views[i]
cpdef int add_views(self, list views) except -1:
self.nr_views += len(strings)
cpdef int add_view(self, unicode view) except -1:
self.nr_views += 1
self.views = <char**>realloc(self.views, self.nr_views * sizeof(utf8_t))
cdef unicode view
cdef bytes utf8_string
for i, view in enumerate(strings):
view = string_views[i]
utf8_string = view.encode('utf8')
# Intern strings, allowing pointer comparison
utf8_string = intern(utf8_string)
self.views[i] = utf8_string
cdef bytes utf8_string = view.encode('utf8')
# Intern strings, allowing pointer comparison
utf8_string = intern(utf8_string)
self.views[self.nr_views - 1] = utf8_string
cpdef bint check_flag(self, size_t flag_id) except *:
"""Access the value of one of the pre-computed boolean distribution features.
@ -92,154 +85,7 @@ cdef class Lexeme:
Meanings depend on the language-specific distributional features being loaded.
The suggested features for latin-alphabet languages are: TODO
"""
assert flag_id < flags.MAX_FLAG
return self.flags & (1 << flag_id)
cpdef int set_flag(self, size_t flag_id) except -1:
assert flag_id < flags.MAX_FLAG
self.flags |= (1 << flag_id)
#
#cdef class CasedWord(Word):
# def __cinit__(self, bytes string, list views):
# Word.__cinit__(self, string, string_views)
#
# cpdef bint is_often_uppered(self) except *:
# '''Check the OFT_UPPER distributional flag for the word.
#
# The OFT_UPPER flag records whether a lower-cased version of the word
# is found in all-upper case frequently in a large sample of text, where
# "frequently" is defined as P >= 0.95 (chosen for high mutual information for
# POS tagging).
#
# Case statistics are estimated from a large text corpus. Estimates are read
# from data/en/case_stats, and can be replaced using spacy.en.load_case_stats.
#
# >>> is_often_uppered(lookup(u'nato'))
# True
# >>> is_often_uppered(lookup(u'the'))
# False
# '''
# return self.dist_flags & (1 << OFT_UPPER)
#
#
# cpdef bint is_often_titled(self) except *:
# '''Check the OFT_TITLE distributional flag for the word.
#
# The OFT_TITLE flag records whether a lower-cased version of the word
# is found title-cased (see string.istitle) frequently in a large sample of text,
# where "frequently" is defined as P >= 0.3 (chosen for high mutual information for
# POS tagging).
#
# Case statistics are estimated from a large text corpus. Estimates are read
# from data/en/case_stats, and can be replaced using spacy.en.load_case_stats.
#
# >>> is_oft_upper(lookup(u'john'))
# True
# >>> is_oft_upper(lookup(u'Bill'))
# False
# '''
# return self.dist_flags & (1 << OFT_TITLE)
#
#
# cpdef bint is_alpha(self) except *:
# """Check whether all characters in the word's string are alphabetic.
#
# Should match the :py:func:`unicode.isalpha()` function.
#
# >>> is_alpha(lookup(u'Hello'))
# True
# >>> is_alpha(lookup(u'العرب'))
# True
# >>> is_alpha(lookup(u'10'))
# False
# """
# return self.orth_flags & 1 << IS_ALPHA
#
# cpdef bint is_digit(self) except *:
# """Check whether all characters in the word's string are numeric.
#
# Should match the :py:func:`unicode.isdigit()` function.
#
# >>> is_digit(lookup(u'10'))
# True
# >>> is_digit(lookup(u'๐'))
# True
# >>> is_digit(lookup(u'one'))
# False
# """
# return self.orth_flags & 1 << IS_DIGIT
#
# cpdef bint is_punct(self) except *:
# """Check whether all characters belong to a punctuation unicode data category
# for a Lexeme ID.
#
# >>> is_punct(lookup(u'.'))
# True
# >>> is_punct(lookup(u'⁒'))
# True
# >>> is_punct(lookup(u' '))
# False
# """
# return self.orth_flags & 1 << IS_PUNCT
#
# cpdef bint is_space(self) except *:
# """Give the result of unicode.isspace() for a Lexeme ID.
#
# >>> is_space(lookup(u'\\t'))
# True
# >>> is_space(lookup(u'<unicode space>'))
# True
# >>> is_space(lookup(u'Hi\\n'))
# False
# """
# return self.orth_flags & 1 << IS_SPACE
#
# cpdef bint is_lower(self) except *:
# """Give the result of unicode.islower() for a Lexeme ID.
#
# >>> is_lower(lookup(u'hi'))
# True
# >>> is_lower(lookup(<unicode>))
# True
# >>> is_lower(lookup(u'10'))
# False
# """
# return self.orth_flags & 1 << IS_LOWER
#
# cpdef bint is_upper(self) except *:
# """Give the result of unicode.isupper() for a Lexeme ID.
#
# >>> is_upper(lookup(u'HI'))
# True
# >>> is_upper(lookup(u'H10'))
# True
# >>> is_upper(lookup(u'10'))
# False
# """
# return self.orth_flags & 1 << IS_UPPER
#
# cpdef bint is_title(self) except *:
# """Give the result of unicode.istitle() for a Lexeme ID.
#
# >>> is_title(lookup(u'Hi'))
# True
# >>> is_title(lookup(u'Hi1'))
# True
# >>> is_title(lookup(u'1'))
# False
# """
# return self.orth_flags & 1 << IS_TITLE
#
# cpdef bint is_ascii(self) except *:
# """Give the result of checking whether all characters in the string are ascii.
#
# >>> is_ascii(lookup(u'Hi'))
# True
# >>> is_ascii(lookup(u' '))
# True
# >>> is_title(lookup(u'<unicode>'))
# False
# """
# return self.orth_flags & 1 << IS_ASCII