From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)
Postprocess Tokens has 48 facts recorded in Dontopedia across 5 references, with 5 live disagreements.
Mostly:rdf:type(5), returns(4), has parameter(4)
removesfiltersByapplieshasParameterrdfs:labelremovesStopWordsappliesLemmatizationtransformationfilterConditionprocessingOrderOther subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. “X motherOf this subject” — and answer questions the forward facts can't. Grouped by predicate.
containsFunctionContains Function(2)ex:codeBlockex:text_processing_pipelinecalledBeforeCalled Before(1)ex:tokenize_textcallsFunctionCalls Function(1)ex:example_usagehasStepHas Step(1)ex:text_processing_pipelineinputForInput for(1)ex:tokensoutputOfOutput of(1)ex:final_tokensprecedesPrecedes(1)ex:tokenize_textusesFunctionUses Function(1)ex:example_usageThe long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.
| Predicate | Value | Ref |
|---|---|---|
| Parameter Name | tokens | [4] |
| Control Structure | list-comprehension | [4] |
| Follows | Tokenize Text | [4] |
| Two Phase Processing | stop-word-removal-then-lemmatization | [4] |
| Iteration | token-level-processing | [4] |
| Produces | final_tokens | [3] |
| Uses List Comprehension | true | [3] |
| Called by | Example Usage | [3] |
| Accesses | lemma property | [1] |
| Uses Lemma | true | [1] |
| Lemmatizes Tokens | true | [1] |
| Description | Removes stop words and lemmatizes tokens | [1] |
| Depends on | Tokenize Text | [2] |
| Maps | Lemmas | [2] |
| Filters | Stop Words | [2] |
| Second Step | Lemmatize Tokens | [2] |
| First Step | Remove Stop Words | [2] |
Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.
doc:beam/e50e1439-fa74-447d-ba48-a7a4b6694859cleaned_text = re.sub(r"(\bcan't\b)", "cannot", cleaned_text) return cleaned_text def detect_language(text): try: lang = langdetect.detect(text) return lang except langdetect.LangDetectException: ret…
doc:beam/5eed31af-31d4-479c-87b1-892ac460fe9ddetected_lang = detect_language(cleaned_text) tokens = tokenize_text(cleaned_text, detected_lang) final_tokens = postprocess_tokens(tokens) print(final_tokens) ``` ### Explanation 1. **Cache Initialization**: - `cache_location`: Specif…
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