word

as donto believed on

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-11.)

word is Split the text into individual words or tokens.

31 facts·17 predicates·5 sources·5 in dispute

Mostly:rdf:type(5), contrasts with(4), compared to(3)

Inbound mentions (10)

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.

`supportsTask`Supports Task(2)

Nltkex:nltk
Spa Cyex:spaCy

`capability`Capability(1)

Nltkex:NLTK

`containsElement`Contains Element(1)

Methods Listex:methods-list

`containsSubsection`Contains Subsection(1)

Tokenization Sectionex:tokenization-section

`containsTask`Contains Task(1)

Tokenization Sectionex:tokenization-section

`exampleOf`Example of(1)

Basic Text Processing Tasksex:basic-text-processing-tasks

`hasMember`Has Member(1)

Tokenization Methodsex:tokenization-methods

`hasMethod`Has Method(1)

Tokenization Codeex:tokenization-code

`hasSubtype`Has Subtype(1)

Tokenizationex:tokenization

Other facts (27)

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.

27 facts

Predicate	Value	Ref
Rdf:type	Tokenization Method	[1]
Rdf:type	Capability	[2]
Rdf:type	Tokenization Method	[3]
Rdf:type	Tokenization Method	[4]
Rdf:type	Tokenization Method	[5]
Contrasts With	Sentence Tokenization	[5]
Contrasts With	Regex Tokenization	[5]
Contrasts With	Treebank Tokenization	[5]
Contrasts With	Whitespace Tokenization	[5]
Compared to	Sentence Tokenization	[4]
Compared to	Regular Expression Tokenization	[4]
Compared to	Treebank Word Tokenization	[4]
Inverse of	Text Splitting	[1]
Inverse of	Breaks Text Into Individual Words	[3]
Description	Split the text into individual words or tokens	[1]
Method of	Tokenization	[1]
Part of	Tokenization Methods	[3]
Function	Breaks Text Into Individual Words	[3]
Use Case	Basic Text Processing Tasks	[3]
Has Alternative Name	word tokenize	[3]
Category	Basic Tokenization	[3]
List Position	1	[3]
Domain	Basic Nlp Tasks	[3]
Optimal for	Basic Text Processing Tasks	[3]
Uses	Sent Tokenize	[4]
Output Example	['This','is','another','test','sentence.']	[4]
Is Variant of	Tokenization Method	[5]

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.

31 undated

—

typebeam/ea3a17ba-b67f-4340-be36-7ad8b3ad3c6a

ex:TokenizationMethod

—

labelbeam/ea3a17ba-b67f-4340-be36-7ad8b3ad3c6a

Word Tokenization

—

descriptionbeam/ea3a17ba-b67f-4340-be36-7ad8b3ad3c6a

Split the text into individual words or tokens

—

inverseOfbeam/ea3a17ba-b67f-4340-be36-7ad8b3ad3c6a

ex:text-splitting

—

methodOfbeam/ea3a17ba-b67f-4340-be36-7ad8b3ad3c6a

ex:tokenization

—

typebeam/c9e2838c-b8a4-4591-969b-ee77610720de

ex:Capability

—

labelbeam/c9e2838c-b8a4-4591-969b-ee77610720de

Word Tokenization

—

typebeam/397c4f27-eefd-4b7e-b694-fb50a6ade661

ex:TokenizationMethod

—

labelbeam/397c4f27-eefd-4b7e-b694-fb50a6ade661

Word Tokenization

—

partOfbeam/397c4f27-eefd-4b7e-b694-fb50a6ade661

ex:tokenization-methods

—

functionbeam/397c4f27-eefd-4b7e-b694-fb50a6ade661

ex:breaks-text-into-individual-words

—

useCasebeam/397c4f27-eefd-4b7e-b694-fb50a6ade661

ex:basic-text-processing-tasks

—

hasAlternativeNamebeam/397c4f27-eefd-4b7e-b694-fb50a6ade661

word tokenize

—

categorybeam/397c4f27-eefd-4b7e-b694-fb50a6ade661

ex:basic-tokenization

—

inverseOfbeam/397c4f27-eefd-4b7e-b694-fb50a6ade661

ex:breaks-text-into-individual-words

—

listPositionbeam/397c4f27-eefd-4b7e-b694-fb50a6ade661

—

domainbeam/397c4f27-eefd-4b7e-b694-fb50a6ade661

ex:basic-nlp-tasks

—

optimalForbeam/397c4f27-eefd-4b7e-b694-fb50a6ade661

ex:basic-text-processing-tasks

—

typebeam/270c7c4b-2f76-41fb-bfa0-809380b3eed6

ex:TokenizationMethod

—

usesbeam/270c7c4b-2f76-41fb-bfa0-809380b3eed6

ex:sent_tokenize

—

comparedTobeam/270c7c4b-2f76-41fb-bfa0-809380b3eed6

ex:sentence-tokenization

—

comparedTobeam/270c7c4b-2f76-41fb-bfa0-809380b3eed6

ex:regular-expression-tokenization

—

comparedTobeam/270c7c4b-2f76-41fb-bfa0-809380b3eed6

ex:treebank-word-tokenization

—

outputExamplebeam/270c7c4b-2f76-41fb-bfa0-809380b3eed6

['This','is','another','test','sentence.']

—

typebeam/9a84a7b0-f92b-48b9-8c5d-9bcd43c3376f

ex:TokenizationMethod

—

labelbeam/9a84a7b0-f92b-48b9-8c5d-9bcd43c3376f

word

—

isVariantOfbeam/9a84a7b0-f92b-48b9-8c5d-9bcd43c3376f

ex:tokenization-method

—

contrastsWithbeam/9a84a7b0-f92b-48b9-8c5d-9bcd43c3376f

ex:sentence-tokenization

—

contrastsWithbeam/9a84a7b0-f92b-48b9-8c5d-9bcd43c3376f

ex:regex-tokenization

—

contrastsWithbeam/9a84a7b0-f92b-48b9-8c5d-9bcd43c3376f

ex:treebank-tokenization

—

contrastsWithbeam/9a84a7b0-f92b-48b9-8c5d-9bcd43c3376f

ex:whitespace-tokenization

References (5)

5 references

[1]Ea3a17ba B67f 4340 Be36 7ad8b3ad3c6a5 facts
ctx:claims/beam/ea3a17ba-b67f-4340-be36-7ad8b3ad3c6a
- full textbeam-chunk
  text/plain1 KBdoc:beam/ea3a17ba-b67f-4340-be36-7ad8b3ad3c6a
  Show excerpt
  - **Word Tokenization**: Split the text into individual words or tokens. - **Sentence Tokenization**: Split the text into sentences. ### 3. **Named Entity Recognition (NER)** - **Entity Extraction**: Identify and extract named entities suc…
[2]C9e2838c B8a4 4591 969b Ee77610720de2 facts
ctx:claims/beam/c9e2838c-b8a4-4591-969b-ee77610720de
- full textbeam-chunk
  text/plain1 KBdoc:beam/c9e2838c-b8a4-4591-969b-ee77610720de
  Show excerpt
  1. **Hyperparameter Search**: Use grid search or random search to find the best hyperparameters. 2. **Learning Rate Scheduling**: Use learning rate schedulers like `ReduceLROnPlateau` or `CosineAnnealingLR`. ### 4. Ensemble Methods 1. **E…
[3]397c4f27 Eefd 4b7e B694 Fb50a6ade66111 facts
ctx:claims/beam/397c4f27-eefd-4b7e-b694-fb50a6ade661
- full textbeam-chunk
  text/plain1 KBdoc:beam/397c4f27-eefd-4b7e-b694-fb50a6ade661
  Show 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…
[4]270c7c4b 2f76 41fb Bfa0 809380b3eed66 facts
ctx:claims/beam/270c7c4b-2f76-41fb-bfa0-809380b3eed6
[5]9a84a7b0 F92b 48b9 8c5d 9bcd43c3376f7 facts
ctx:claims/beam/9a84a7b0-f92b-48b9-8c5d-9bcd43c3376f
- full textbeam-chunk
  text/plain1 KBdoc:beam/9a84a7b0-f92b-48b9-8c5d-9bcd43c3376f
  Show excerpt
  methods = ['word', 'sentence', 'regex', 'treebank', 'whitespace'] for method in methods: tokens = tokenize_text(text, method) print(f"{method.capitalize()} Tokenization: {tokens}") ``` ### Summary By using NLTK's various tokenizat…

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word

Inbound mentions (10)

supportsTaskSupports Task(2)

capabilityCapability(1)

containsElementContains Element(1)

containsSubsectionContains Subsection(1)

containsTaskContains Task(1)

exampleOfExample of(1)

hasMemberHas Member(1)

hasMethodHas Method(1)

hasSubtypeHas Subtype(1)

Other facts (27)

Timeline

References (5)

See also

Keep researching

`supportsTask`Supports Task(2)

`capability`Capability(1)

`containsElement`Contains Element(1)

`containsSubsection`Contains Subsection(1)

`containsTask`Contains Task(1)

`exampleOf`Example of(1)

`hasMember`Has Member(1)

`hasMethod`Has Method(1)

`hasSubtype`Has Subtype(1)