spaCy pipeline component for spelling correction using sysmepll.
# spaCy Symspell ## Spelling correction implementation in spaCy via Symspell
This package is a [spaCy 2.0 extension](https://spacy.io/usage/processing-pipelines#section-extensions) that adds sentnece/spelling corrections via Symspell to spaCy’s text processing pipeline.
pip install spacy_symspell
## Notes This package is still in Alpha and there may be unforeseen errors. Dictionary loading time is also significant, can take up to 30 seconds on slow machines.
Adding the component to the processing pipeline is relatively simple:
import spacy from spacy_symspell import SpellingCorrector
nlp = spacy.load(‘en_core_web_sm’) corrector = SpellingCorrector() nlp.add_pipe(corrector) doc = nlp(‘What doyuoknowabout antyhing’)
- for s in doc._.suggestions:#iterable
- print(s) #What doyon about anything
doc._.segmentation #::segmented_string - What doyouk now about antyhing ::corrected_string - that dook now about anything
spaCy_symspell operates on Doc and Span spaCy objects. When called on a Doc or Span, the object is given two attributes: suggestions (a list of all found spelling suggestions) and segmentation (a corrected sentence in the case of ommitted spaces).
## Todo Symspell accuracy can be improved with the help of spaCy by extracting and analyzing resulting n-grams and cross-referencing with possible n-grams deductible from the character groups in the symspell result. For example the correction ‘that dook now’ leaves us with a verbless sentence, and on closer analysis will reveal that the character group ‘now’ is related with the verb ‘know’, and the verb know is associated with the n-gram ‘you know’.
## Under the hood [spacy_symspell](https://github.com/xwiz/spacy_symspell) is currently a wrapper of the [python port](https://github.com/mammothb/symspellpy) for [Symspell](https://github.com/wolfgarbe/SymSpell). For additional details, see the linked project pages.
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