Dontopedia

Function Return Type

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

Function Return Type has 7 facts recorded in Dontopedia across 2 references, with 2 live disagreements.

7 facts·5 predicates·2 sources·2 in dispute

Mostly:rdf:type(2), includes(2), return type(1)

Maturity scale raw canonical shape-checked rule-derived certified

Other facts (7)

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.

7 facts
PredicateValueRef
Rdf:typeUnion Type[1]
Rdf:typeReturn Type Specification[2]
Includeslist-of-strings[1]
IncludesNoneType[1]
Return TypeTuple Corrected Query and Time[2]
First Return TypeString[2]
Second Return TypeFloat[2]

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.

typebeam/e031adb5-dbba-404f-9b4c-7a60e2566ca4
ex:UnionType
includesbeam/e031adb5-dbba-404f-9b4c-7a60e2566ca4
list-of-strings
includesbeam/e031adb5-dbba-404f-9b4c-7a60e2566ca4
NoneType
typebeam/8f327b3d-bdda-4eb4-8da7-5bd63a1fcd03
ex:ReturnTypeSpecification
returnTypebeam/8f327b3d-bdda-4eb4-8da7-5bd63a1fcd03
ex:tuple-corrected-query-and-time
firstReturnTypebeam/8f327b3d-bdda-4eb4-8da7-5bd63a1fcd03
ex:String
secondReturnTypebeam/8f327b3d-bdda-4eb4-8da7-5bd63a1fcd03
ex:Float

References (2)

2 references
  1. ctx:claims/beam/e031adb5-dbba-404f-9b4c-7a60e2566ca4
    • full textbeam-chunk
      text/plain1 KBdoc:beam/e031adb5-dbba-404f-9b4c-7a60e2566ca4
      Show excerpt
      ```python import spacy # Load the SpaCy model nlp = spacy.load("en_core_web_sm") # Define a function to tokenize text def tokenize_text(text): try: doc = nlp(text) tokens = [token.text for token in doc] return
  2. ctx:claims/beam/8f327b3d-bdda-4eb4-8da7-5bd63a1fcd03
    • full textbeam-chunk
      text/plain1 KBdoc:beam/8f327b3d-bdda-4eb4-8da7-5bd63a1fcd03
      Show excerpt
      Based on the analysis, we can make targeted optimizations to improve performance. ### Example Code with Profiling Here's an example of how you can profile your code to identify the bottleneck: ```python import time import cProfile import

See also

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