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Match tokenized words and phrases within the original, untokenized, often messy, text.

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The purpose of the module Match is to get the offsets (as well as the string between those offsets, for debugging) of a cleaned-up, tokenized string from its original, untokenized source. “Big deal,” you might say, but this is actually a pretty difficult task if the original text is sufficiently messy, not to mention rife with Unicode characters.

Consider some text, stored in a variable original_text, like:

I   am writing a letter !  Sometimes,I forget to put spaces (and do weird stuff with punctuation)  ?  J'aurai une pomme, s'il vous plâit !

This will/should/might be properly tokenized as:

[['I', 'am', 'writing', 'a', 'letter', '!'],
 ['Sometimes', ',', 'I', 'forget', 'to', 'put', 'spaces', '-LRB-', 'and', 'do', 'weird', 'stuff', 'with', 'punctuation', '-RRB-', '?'],
 ["J'aurai", 'une', 'pomme', ',', "s'il", 'vous', 'plâit', '!']]


In [2]: import match

In [3]: match.match(original_text, ['-LRB-', 'and', 'do', 'weird', 'stuff', 'with', 'punctuation', '-RRB-'])
Out[3]: [(60, 97, '(and do weird stuff with punctuation)')]

In [4]: match.match(original_text, ['I', 'am', 'writing', 'a', 'letter', '!'])
Out[4]: [(0, 25, 'I   am writing a letter !')]

In [5]: match.match(original_text, ["s'il", 'vous', 'plâit', '!'])
Out[5]: [(121, 138, "s'il vous plâit !")]

The return type from match() is a list because it will return all occurrences of the argument, be it a list of tokens or a single string (word):

In [6]: match.match(original_text, "I")
Out[6]: [(0, 1, 'I'), (37, 38, 'I')]

When passing in a single string, match() is expecting that string to be a single word or token. Thus:

In [7]: match.match("****because,the****", "because , the")
Out[7]: []

Try passing in "because , the".split(' ') instead, or better yet, the output from a proper tokenizer.

For convenience, a function called match_lines() is provided:

In [8]: match.match_lines(original_text, [
   ...: ['-LRB-', 'and', 'do', 'weird', 'stuff', 'with', 'punctuation', '-RRB-'],
   ...: ['I', 'am', 'writing', 'a', 'letter', '!'],
   ...: "I"
   ...: ])
[(0, 1, 'I'),
 (0, 25, 'I   am writing a letter !'),
 (37, 38, 'I'),
 (60, 97, '(and do weird stuff with punctuation)')]

The values returned will always be sorted by their offsets.


pip install match or conda install -c ets match




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