get indices of original text from nltk word_tokenize
You can also do this:
def spans(txt):
tokens=nltk.word_tokenize(txt)
offset = 0
for token in tokens:
offset = txt.find(token, offset)
yield token, offset, offset+len(token)
offset += len(token)
s = "And now for something completely different and."
for token in spans(s):
print token
assert token[0]==s[token[1]:token[2]]
And get:
('And', 0, 3)
('now', 4, 7)
('for', 8, 11)
('something', 12, 21)
('completely', 22, 32)
('different', 33, 42)
('.', 42, 43)
I think you are looking for is the span_tokenize()
method.
Apparently this is not supported by the default tokenizer.
Here is a code example with another tokenizer.
from nltk.tokenize import WhitespaceTokenizer
s = "Good muffins cost $3.88\nin New York."
span_generator = WhitespaceTokenizer().span_tokenize(s)
spans = [span for span in span_generator]
print(spans)
Which gives:
[(0, 4), (5, 12), (13, 17), (18, 23), (24, 26), (27, 30), (31, 36)]
just getting the offsets:
offsets = [span[0] for span in spans]
[0, 5, 13, 18, 24, 27, 31]
For further information (on the different tokenizers available) see the tokenize api docs