Comments (3)
It's not designed to do that. WordSegment is for transforming "wheninthecourseofhumanevents" into ["when", "in", "the", "course", "of", "human", "events"]. It doesn't do anything more than that. In your case, the value "I'm from New York." was cleaned as "imfromnewyork" and then segmented.
Sorry, it doesn't parse bigrams. Was there something in the docs that was misleading or confusing?
from python-wordsegment.
inside README.md's features,
it says "Includes unigram and bigram data"
I'm confused as in why bigram data is there without anything using it?
from python-wordsegment.
The algorithm does use the bigram data. See the score
function for details: https://github.com/grantjenks/wordsegment/blob/master/wordsegment.py#L63 The comment there reads:
# Conditional probability of the word given the previous
# word. The technical name is *stupid backoff* and it's
# not a probability distribution but it works well in
# practice.
And you can learn more about stupid backoff in http://www.aclweb.org/anthology/D07-1090.pdf
Bigrams data is also useful for exploration, like comparing "in the" and "in a":
>>> import wordsegment
>>> wordsegment.load()
>>> wordsegment.BIGRAMS['in the']
1628795324.0
>>> wordsegment.BIGRAMS['in a']
364730082.0
from python-wordsegment.
Related Issues (20)
- ZeroDivisionError HOT 2
- License question HOT 7
- max() arg is an empty sequence HOT 1
- How to add custom values? HOT 1
- unigrams HOT 1
- import error HOT 2
- Return a list of the most probable segmentations. HOT 3
- Text with numbers doesn't segment as expected HOT 3
- `exhilarate` does not segment as expected HOT 1
- Can I use this from C or C++? HOT 1
- Please allow separation of numbers from text HOT 1
- Corpus python HOT 1
- russian language HOT 2
- Training on new, modern data. HOT 1
- feature_request(mode): preserve all punctuation marks HOT 2
- Support for Other Languages HOT 2
- RecursionError on segment call HOT 6
- 'helloworld' does not segment as expected HOT 3
- Words segmenting in one direction, but not another. HOT 1
- Using with Additional corpus of spelling mistakes. HOT 3
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