ReplaCy = spaCy Matcher + pyInflect. Create rules, correct sentences.
We found that in multiple projects we had duplicate code for using spaCy’s blazing fast matcher to do the same thing: Match-Replace-Grammaticalize. So we wrote replaCy!
Match - spaCy’s matcher is great, and lets you match on text, shape, POS, dependency parse, and other features. We extended this with “match hooks”, predicates that get used in the callback function to further refine a match.
Replace - Not built into spaCy’s matcher syntax, but easily added. You often want to replace a matched word with some other term.
Grammaticalize - If you match on ”LEMMA”: “dance”, and replace with suggestions: ["sing"], but the actual match is danced, you need to conjugate “sing” appropriately. This is the “killer feature” of replaCy
spacy >= 2.0(not installed by default, expected nlp object)
pip install replacy
from replacy import ReplaceMatcher import spacy # load nlp spacy model of your choice nlp = spacy.load("en_core_web_sm") rmatcher = ReplaceMatcher(nlp) # get inflected suggestions # look up the first suggestion span = rmatcher("She extracts revenge.") span._.suggestions # >>> ['exacts']
Testing match_dict (json schema validation)
from replacy import ReplaceMatcher from replacy.db import load_json match_dict = load_json('/path/to/your/match/dict') ReplaceMatcher.validate_match_dict(match_dict)
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