False
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)
False has 12 facts recorded in Dontopedia across 9 references, with 1 live disagreement.
12 facts·2 predicates·9 sources·1 in dispute
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (15)
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.
returnsReturns(4)
- False Return
ex:false-return - Send to Kafka
ex:send-to-kafka - Should Erase Data Function
ex:should-erase-data-function - Validate Document
ex:validate_document
returnsOnFailureReturns on Failure(3)
- Check Access Function
ex:check-access-function - Check Security
ex:check-security - Update Priority Function
ex:update-priority-function
returnsValueReturns Value(2)
- Return False
ex:return-false - Store Data
ex:store_data
hasReturnValueHas Return Value(1)
- Save Model Function
ex:save-model-function
possibleReturnValuesPossible Return Values(1)
- Validation Functions
ex:validation-functions
resultsInResults in(1)
- Validation Failure
ex:validation-failure
returnsFalseForUnknownFieldReturns False for Unknown Field(1)
- Validate Value
ex:_validate-value
returnsLiteralReturns Literal(1)
- Has Access Function
ex:has-access-function
returnsOnMismatchReturns on Mismatch(1)
- Authenticate User
authenticate-user
Other facts (9)
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.
9 facts
| Predicate | Value | Ref |
|---|---|---|
| Rdf:type | Python Boolean | [1] |
| Rdf:type | Return Value | [3] |
| Rdf:type | Boolean | [4] |
| Rdf:type | Boolean Value | [5] |
| Rdf:type | Boolean | [6] |
| Rdf:type | Boolean Value | [7] |
| Rdf:type | Data Type | [8] |
| Rdf:type | Boolean Literal | [9] |
| Used in | validation return | [7] |
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.
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typebeam/401284ac-4b49-4678-a3e2-aa44c5ceacbb
ex:PythonBoolean
—
labelbeam/c690200f-f62a-49e2-89ad-0e73ca8b44ed
False
—
typebeam/73db6035-02e5-47c3-8506-076dd04c43ef
ex:ReturnValue
—
typebeam/b862b73d-2ef7-4af9-bba9-00aa77986265
ex:Boolean
—
typebeam/a406710d-0992-4857-a2c3-8d51ffe02217
ex:BooleanValue
—
labelbeam/a406710d-0992-4857-a2c3-8d51ffe02217
False
—
typebeam/0479e080-b49a-437c-a771-7e49cf7099de
ex:Boolean
—
typebeam/bc0a9ad5-73aa-4263-b11e-dbb75c03c15d
ex:BooleanValue
—
usedInbeam/bc0a9ad5-73aa-4263-b11e-dbb75c03c15d
validation return
—
typebeam/e24dc3e9-d3c9-4c87-9eb2-f49f89b411ff
ex:DataType
—
typebeam/dbb91cd4-736d-4452-9b19-46651567b10b
ex:BooleanLiteral
—
labelbeam/dbb91cd4-736d-4452-9b19-46651567b10b
False
References (9)
9 references
ctx:claims/beam/401284ac-4b49-4678-a3e2-aa44c5ceacbb- full textbeam-chunktext/plain1 KB
doc:beam/401284ac-4b49-4678-a3e2-aa44c5ceacbbShow excerpt
print(f"Adjusted nprobe search time: {end_time - start_time:.2f} seconds") ``` By systematically adjusting these parameters, you can find the optimal configuration that balances search speed and accuracy for your application. [Turn 1978] …
ctx:claims/beam/c690200f-f62a-49e2-89ad-0e73ca8b44ed- full textbeam-chunktext/plain1 KB
doc:beam/c690200f-f62a-49e2-89ad-0e73ca8b44edShow excerpt
try: future = producer.send(topic, value=data) record_metadata = future.get(timeout=10) # Wait for the message to be sent print(f"Message sent to topic {record_metadata.topic}, partition {record_…
ctx:claims/beam/73db6035-02e5-47c3-8506-076dd04c43efctx:claims/beam/b862b73d-2ef7-4af9-bba9-00aa77986265- full textbeam-chunktext/plain1 KB
doc:beam/b862b73d-2ef7-4af9-bba9-00aa77986265Show excerpt
redlock = Redlock([{"host": "localhost", "port": 6379, "db": 0}]) def save_model(version, data): lock_name = f"model_{version}_lock" lock = redlock.lock(lock_name, 10000) # Lock duration in milliseconds if not l…
ctx:claims/beam/a406710d-0992-4857-a2c3-8d51ffe02217ctx:claims/beam/0479e080-b49a-437c-a771-7e49cf7099dectx:claims/beam/bc0a9ad5-73aa-4263-b11e-dbb75c03c15dctx:claims/beam/e24dc3e9-d3c9-4c87-9eb2-f49f89b411ff- full textbeam-chunktext/plain1 KB
doc:beam/e24dc3e9-d3c9-4c87-9eb2-f49f89b411ffShow excerpt
correction_module.load_dictionary(dictionary_data) query = "I'm loking for a way to improove my spelng" corrected_query = correction_module.correct_spelling(query) print(corrected_query) # Output: "I'm looking for a way to improve my spel…
ctx:claims/beam/dbb91cd4-736d-4452-9b19-46651567b10b- full textbeam-chunktext/plain1 KB
doc:beam/dbb91cd4-736d-4452-9b19-46651567b10bShow excerpt
Here's an example of how you can implement these best practices in Python: #### 1. Use Efficient Data Structures ```python class TrieNode: def __init__(self): self.children = {} self.is_end_of_word = False class Trie:…
See also
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