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spaCy pipeline component for spelling correction using sysmepll.

Project description

# spaCy Symspell ## Spelling correction implementation in spaCy via Symspell

This package is a [spaCy 2.0 extension]( that adds sentnece/spelling corrections via Symspell to spaCy’s text processing pipeline.

## Installation

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.

## Usage

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]( is currently a wrapper of the [python port]( for [Symspell]( For additional details, see the linked project pages.

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