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Exclude math and modifier symbols as tokens

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Former-commit-id: 8f3c9f576c
This commit is contained in:
Robyn Speer 2015-08-25 11:43:22 -04:00
parent 8637aaef9e
commit 070c89c00c
1 changed files with 6 additions and 5 deletions
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11
wordfreq/tokens.py
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@ -4,10 +4,11 @@ import unicodedata
# Here's what the following regular expression is looking for:
#
# At the start, it looks for a character in the set [\S--\p{punct}]. \S
# contains non-space characters, and then it subtracts the set of Unicode
# punctuation characters from that set. This is slightly different from \w,
# because it leaves symbols (such as emoji) as tokens.
# At the start, it looks for a character in the set \S -- the set of
# non-punctuation -- with various characters subtracted out, including punctuation
# and most of the 'symbol' categories. (We leave So, "Symbol - Other", because
# it contains things like emoji that have interesting frequencies. This is why
# we don't just insist on the token starting with a "word" character, \w.)
#
# After it has found one such character, the rest of the token is (?:\B\S)*,
# which continues to consume characters as long as the next character does not
@ -26,7 +27,7 @@ import unicodedata
# correct behavior for word-wrapping, but it's an ugly failure mode for NLP
# tokenization.
TOKEN_RE = regex.compile(r'[\S--\p{punct}](?:\B\S|[\p{IsIdeo}\p{Script=Hiragana}])*', regex.V1 | regex.WORD)
TOKEN_RE = regex.compile(r'[\S--[\p{punct}\p{Sm}\p{Sc}\p{Sk}]](?:\B\S|[\p{IsIdeo}\p{Script=Hiragana}])*', regex.V1 | regex.WORD)
ARABIC_MARK_RE = regex.compile(r'[[\p{Mn}&&\p{Block=Arabic}]\N{ARABIC TATWEEL}]', regex.V1)