Postprocessing
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)
Postprocessing is Basic stop word removal and lemmatization.
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- Simple Sequential Design
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- Tokenization
ex:tokenization
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References (3)
ctx:claims/beam/910d6fc8-8228-4a97-97e1-5c2720f7f34e- full textbeam-chunktext/plain1 KB
doc:beam/910d6fc8-8228-4a97-97e1-5c2720f7f34eShow excerpt
- **Objective**: Clean up and standardize the tokenized output. - **Tasks**: - Remove stop words. - Lemmatize or stem tokens. - Handle edge cases and errors. - **Tools**: `spaCy`, custom postprocessing functions. ##…
ctx:claims/beam/682fcc87-6770-4bd6-b81b-3048d4338e0ectx:claims/beam/19c50864-0395-4826-b4c8-6b6c2fab4d44- full textbeam-chunktext/plain1 KB
doc:beam/19c50864-0395-4826-b4c8-6b6c2fab4d44Show excerpt
return lang def tokenize_text(text, lang): if lang == 'en': doc = nlp_en(text) tokens = [token.text for token in doc] elif lang == 'es': doc = nlp_es(text) tokens = [token.text for token in doc] …
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