Nltk Import
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-11.)
Nltk Import has 11 facts recorded in Dontopedia across 4 references, with 3 live disagreements.
Mostly:rdf:type(4), imports(4), import statement(2)
Maturity scale
raw canonical shape-checked rule-derived certifiedOther facts (11)
The 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 |
|---|---|---|
| Rdf:type | Python Import | [1] |
| Rdf:type | Code Statement | [2] |
| Rdf:type | Import Statement | [3] |
| Rdf:type | Python Import | [4] |
| Imports | word_tokenize | [4] |
| Imports | sent_tokenize | [4] |
| Imports | RegexpTokenizer | [4] |
| Imports | TreebankWordTokenizer | [4] |
| Import Statement | Nltk | [2] |
| Import Statement | Nltk Tokenize | [2] |
| Imports Module | Nltk Module | [3] |
Timeline
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.
References (4)
ctx:claims/beam/29ef79f2-e204-4a4e-866a-e1208290c4f9- full textbeam-chunktext/plain1 KB
doc:beam/29ef79f2-e204-4a4e-866a-e1208290c4f9Show excerpt
reformulated_query = " ".join(reformulated_tokens) return reformulated_query # Test the function query = "the quick brown fox jumps over the lazy dog" reformulated_query = reformulate_query(query) print(reformulated_query) ```…
ctx:claims/beam/397c4f27-eefd-4b7e-b694-fb50a6ade661- full textbeam-chunktext/plain1 KB
doc:beam/397c4f27-eefd-4b7e-b694-fb50a6ade661Show excerpt
NLTK offers several tokenization methods, including word tokenization, sentence tokenization, and more specialized tokenization techniques. Here are five common approaches you can use: 1. **Word Tokenization**: - Breaks text into indivi…
ctx:claims/beam/480c6d5f-104b-4404-ba2b-5c38ac7d8e27- full textbeam-chunktext/plain1 KB
doc:beam/480c6d5f-104b-4404-ba2b-5c38ac7d8e27Show excerpt
```python def tokenize_text_whitespace(text): tokens = text.split() return tokens # Test the function text = "This is another test sentence." tokens = tokenize_text_whitespace(text) print(tokens) ``` ### Integrating with Existing …
ctx:claims/beam/9a78785f-feba-4eb1-89ec-b1d2f293020e
See also
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