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Strip apostrophes from edges of tokens

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The issue here is that if you had French text with an apostrophe,
such as "d'un", it would split it into "d'" and "un", but if "d'"
were re-tokenized it would come out as "d". Stripping apostrophes
makes the process more idempotent.


Former-commit-id: 5a1fc00aaa
This commit is contained in:
Robyn Speer 2015-08-25 12:41:48 -04:00
parent 0b282c5055
commit b22a4b0f02
3 changed files with 7 additions and 2 deletions
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2
wordfreq/tokens.py
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@ -49,7 +49,7 @@ def simple_tokenize(text):
relatively untokenized. relatively untokenized.
""" """
text = unicodedata.normalize('NFC', text) text = unicodedata.normalize('NFC', text)
return [token.casefold() for token in TOKEN_RE.findall(text)] return [token.strip("'").casefold() for token in TOKEN_RE.findall(text)]
def remove_arabic_marks(text): def remove_arabic_marks(text):

2
wordfreq_builder/tests/test_tokenizer.py
View File

@ -6,7 +6,7 @@ def test_tokenizer_1():
text = '"This is a test," she said, "and I\'ll bet y\'all $3.50 that it won\'t fail."' text = '"This is a test," she said, "and I\'ll bet y\'all $3.50 that it won\'t fail."'
tokens = [ tokens = [
'this', 'is', 'a', 'test', 'she', 'said', 'this', 'is', 'a', 'test', 'she', 'said',
'and', "i'll", 'bet', "y'all", '3', '50', 'that', 'and', "i'll", 'bet', "y", "all", '3.50', 'that',
'it', "won't", 'fail', 'it', "won't", 'fail',
] ]
result = cld2_surface_tokenizer(text) result = cld2_surface_tokenizer(text)

5
wordfreq_builder/wordfreq_builder/word_counts.py
View File

@ -6,6 +6,10 @@ import math
import csv import csv
import msgpack import msgpack
import gzip import gzip
import regex
URL_RE = regex.compile(r'https?://(?:\B\S)+')
def count_tokens(filename): def count_tokens(filename):
@ -18,6 +22,7 @@ def count_tokens(filename):
counts = defaultdict(int) counts = defaultdict(int)
with open(filename, encoding='utf-8', errors='replace') as infile: with open(filename, encoding='utf-8', errors='replace') as infile:
for line in infile: for line in infile:
line = URL_RE.sub('', line.strip())
for token in simple_tokenize(line): for token in simple_tokenize(line):
counts[token] += 1 counts[token] += 1