Custom Tokenizer
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-05.)
Custom Tokenizer has 11 facts recorded in Dontopedia across 2 references, with 2 live disagreements.
Mostly:configured with(3), rdf:type(2), variable name(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (2)
Other 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.
definedBeforeDefined Before(1)
- Regex Patterns
ex:regex-patterns
hasTokenizerHas Tokenizer(1)
- Nlp
ex:nlp
Other 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 |
|---|---|---|
| Configured With | Prefix Regex | [1] |
| Configured With | Suffix Regex | [1] |
| Configured With | Infix Regex | [1] |
| Rdf:type | Tokenizer | [1] |
| Rdf:type | Spacy Tokenizer | [2] |
| Variable Name | custom_tokenizer | [1] |
| Replaces | Default Tokenizer | [1] |
| Designed for | edge case handling | [1] |
| Inherits From | Default Tokenizer | [1] |
| Extends | default tokenization behavior | [1] |
| Uses Vocabulary | Nlp Vocab | [2] |
Timeline
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References (2)
ctx:claims/beam/92244a54-f60e-4ad8-a24d-0d7d5323814b- full textbeam-chunktext/plain1 KB
doc:beam/92244a54-f60e-4ad8-a24d-0d7d5323814bShow excerpt
First, ensure you have spaCy installed and download the language model you want to use. For English, you can use the `en_core_web_sm` model. ```bash pip install spacy python -m spacy download en_core_web_sm ``` ### Step 2: Import spaCy an…
ctx:claims/beam/18306c1f-b51a-45dd-b169-e340e3696b52- full textbeam-chunktext/plain1 KB
doc:beam/18306c1f-b51a-45dd-b169-e340e3696b52Show excerpt
Now, let's tokenize some text and visualize the process for debugging. ```python # Sample text text = "Hello, world! This is a test sentence with [custom] tokens." # Process the text doc = nlp(text) # Print the tokens for token in doc: …
See also
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