def combined_rule_prefixes() -> List[str]:
"""Helper function that returns the prefix pattern for the tokenizer.
It is a helper function to accommodate spacy tests that only test
prefixes.
"""
prefix_punct = char_classes.PUNCT.replace("|", " ")
prefixes = (["§", "%", "=", r"\+"] +
char_classes.split_chars(prefix_punct) +
char_classes.LIST_ELLIPSES + char_classes.LIST_QUOTES +
char_classes.LIST_CURRENCY + char_classes.LIST_ICONS)
return prefixes
def combined_rule_prefixes() -> List[str]:
"""Helper function that returns the prefix pattern for the tokenizer.
It is a helper function to accomodate spacy tests that only test
prefixes.
"""
# add lookahead assertions for brackets (may not work properly for unbalanced brackets)
prefix_punct = char_classes.PUNCT.replace("|", " ")
prefix_punct = prefix_punct.replace(r"\(", r"\((?![^\(\s]+\)\S+)")
prefix_punct = prefix_punct.replace(r"\[", r"\[(?![^\[\s]+\]\S+)")
prefix_punct = prefix_punct.replace(r"\{", r"\{(?![^\{\s]+\}\S+)")
prefixes = (["§", "%", "=", r"\+"] +
char_classes.split_chars(prefix_punct) +
char_classes.LIST_ELLIPSES + char_classes.LIST_QUOTES +
char_classes.LIST_CURRENCY + char_classes.LIST_ICONS)
return prefixes
def combined_rule_tokenizer(nlp: Language) -> Tokenizer:
"""Creates a custom tokenizer on top of spaCy's default tokenizer. The
intended use of this function is to replace the tokenizer in a spaCy
pipeline like so:
nlp = spacy.load("some_spacy_model")
nlp.tokenizer = combined_rule_tokenizer(nlp)
@param nlp: a loaded spaCy model
"""
# remove the first hyphen to prevent tokenization of the normal hyphen
hyphens = char_classes.HYPHENS.replace("-|", "", 1)
infixes = (
char_classes.LIST_ELLIPSES + char_classes.LIST_ICONS + [
r"×", # added this special x character to tokenize it separately
r"(?<=[0-9])[+\-\*^](?=[0-9-])",
r"(?<=[{al}])\.(?=[{au}])".format(al=char_classes.ALPHA_LOWER,
au=char_classes.ALPHA_UPPER),
r"(?<=[{a}]),(?=[{a}])".format(a=char_classes.ALPHA),
r'(?<=[{a}])[?";:=,.]*(?:{h})(?=[{a}])'.format(
a=char_classes.ALPHA, h=hyphens),
# removed / to prevent tokenization of /
r'(?<=[{a}"])[:<>=](?=[{a}])'.format(a=char_classes.ALPHA),
])
prefixes = combined_rule_prefixes()
# add the last apostrophe
quotes = char_classes.LIST_QUOTES.copy() + ["’"]
# add lookbehind assertions for brackets (may not work properly for unbalanced brackets)
suffix_punct = char_classes.PUNCT.replace("|", " ")
# These lookbehinds are commented out because they are variable width lookbehinds, and as of spacy 2.1,
# spacy uses the re package instead of the regex package. The re package does not support variable width
# lookbehinds. Hacking spacy internals to allow us to use the regex package is doable, but would require
# creating our own instance of the language class, with our own Tokenizer class, with the from_bytes method
# using the regex package instead of the re package
# suffix_punct = suffix_punct.replace(r"\)", r"(?<!\S+\([^\)\s]+)\)")
# suffix_punct = suffix_punct.replace(r"\]", r"(?<!\S+\[[^\]\s]+)\]")
# suffix_punct = suffix_punct.replace(r"\}", r"(?<!\S+\{[^\}\s]+)\}")
suffixes = (
char_classes.split_chars(suffix_punct) + char_classes.LIST_ELLIPSES +
quotes + char_classes.LIST_ICONS +
["'s", "'S", "’s", "’S", "’s", "’S"] + [
r"(?<=[0-9])\+",
r"(?<=°[FfCcKk])\.",
r"(?<=[0-9])(?:{})".format(char_classes.CURRENCY),
# this is another place where we used a variable width lookbehind
# so now things like 'H3g' will be tokenized as ['H3', 'g']
# previously the lookbehind was (^[0-9]+)
r"(?<=[0-9])(?:{u})".format(u=char_classes.UNITS),
r"(?<=[0-9{}{}(?:{})])\.".format(char_classes.ALPHA_LOWER,
r"%²\-\)\]\+", "|".join(quotes)),
# add |\d to split off the period of a sentence that ends with 1D.
r"(?<=[{a}|\d][{a}])\.".format(a=char_classes.ALPHA_UPPER),
])
infix_re = compile_infix_regex(infixes)
prefix_re = compile_prefix_regex(prefixes)
suffix_re = compile_suffix_regex(suffixes)
# Update exclusions to include these abbreviations so the period is not split off
exclusions = {
abbreviation: [{
ORTH: abbreviation
}]
for abbreviation in ABBREVIATIONS
}
tokenizer_exceptions = nlp.Defaults.tokenizer_exceptions.copy()
tokenizer_exceptions.update(exclusions)
tokenizer = Tokenizer(
nlp.vocab,
tokenizer_exceptions,
prefix_search=prefix_re.search,
suffix_search=suffix_re.search,
infix_finditer=infix_re.finditer,
token_match=nlp.tokenizer.token_match,
)
return tokenizer
def combined_rule_tokenizer(nlp: Language) -> Tokenizer:
"""Creates a custom tokenizer on top of spaCy's default tokenizer. The
intended use of this function is to replace the tokenizer in a spaCy
pipeline like so:
nlp = spacy.load("some_spacy_model")
nlp.tokenizer = combined_rule_tokenizer(nlp)
@param nlp: a loaded spaCy model
"""
# remove the first hyphen to prevent tokenization of the normal hyphen
hyphens = char_classes.HYPHENS.replace("-|", "", 1)
infixes = (
char_classes.LIST_ELLIPSES + char_classes.LIST_ICONS + [
r'×', # added this special x character to tokenize it separately
r'(?<=[0-9])[+\-\*^](?=[0-9-])',
r'(?<=[{}])\.(?=[{}])'.format(char_classes.ALPHA_LOWER,
char_classes.ALPHA_UPPER),
r'(?<=[{a}]),(?=[{a}])'.format(a=char_classes.ALPHA),
r'(?<=[{a}])[?";:=,.]*(?:{h})(?=[{a}])'.format(
a=char_classes.ALPHA, h=hyphens),
# removed / to prevent tokenization of /
r'(?<=[{a}"])[:<>=](?=[{a}])'.format(a=char_classes.ALPHA)
])
prefixes = combined_rule_prefixes()
# add the last apostrophe
quotes = char_classes.QUOTES.replace('|', ' ') + " ’"
# add lookbehind assertions for brackets (may not work properly for unbalanced brackets)
suffix_punct = char_classes.PUNCT.replace('|', ' ')
suffix_punct = suffix_punct.replace(r"\)", r"(?<!\S+\([^\)\s]+)\)")
suffix_punct = suffix_punct.replace(r"\]", r"(?<!\S+\[[^\]\s]+)\]")
suffix_punct = suffix_punct.replace(r"\}", r"(?<!\S+\{[^\}\s]+)\}")
suffixes = (
char_classes.split_chars(suffix_punct) + char_classes.LIST_ELLIPSES +
char_classes.split_chars(quotes) + char_classes.LIST_ICONS +
["'s", "'S", "’s", "’S", "’s", "’S"] + [
r'(?<=[0-9])\+',
r'(?<=°[FfCcKk])\.',
r'(?<=[0-9])(?:{})'.format(char_classes.CURRENCY),
# add to look behind to exclude things like h3g from splitting off the g as a unit
r'(?<=(^[0-9]+|\s{p}*[0-9]+))(?:{u})'.format(u=char_classes.UNITS,
p=prefixes),
r'(?<=[0-9{}{}(?:{})])\.'.format(char_classes.ALPHA_LOWER,
r'%²\-\)\]\+',
char_classes.merge_chars(quotes)),
# add |\d to split off the period of a sentence that ends with 1D.
r'(?<=[{a}|\d][{a}])\.'.format(a=char_classes.ALPHA_UPPER)
])
infix_re = compile_infix_regex(infixes)
prefix_re = compile_prefix_regex(prefixes)
suffix_re = compile_suffix_regex(suffixes)
# Update exclusions to include these abbreviations so the period is not split off
exclusions = {
abbreviation: [{
ORTH: abbreviation
}]
for abbreviation in ABBREVIATIONS
}
tokenizer_exceptions = nlp.Defaults.tokenizer_exceptions.copy()
tokenizer_exceptions.update(exclusions)
tokenizer = Tokenizer(nlp.vocab,
tokenizer_exceptions,
prefix_search=prefix_re.search,
suffix_search=suffix_re.search,
infix_finditer=infix_re.finditer,
token_match=nlp.tokenizer.token_match)
return tokenizer