Dontopedia

create_collection

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-07.)

create_collection has 5 facts recorded in Dontopedia across 2 references, with 2 live disagreements.

5 facts·2 predicates·2 sources·2 in dispute
Maturity scale raw canonical shape-checked rule-derived certified

Inbound 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.

containsFunctionCallContains Function Call(1)

mentionsMentions(1)

Other facts (4)

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.

4 facts
PredicateValueRef
Rdf:typeFunction[1]
Rdf:typeApi Function[2]
Has ParameterName Parameter[1]
Has ParameterDimension Parameter[1]

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/3063fb63-164c-4240-8dd2-02fff0c52172
ex:Function
labelbeam/3063fb63-164c-4240-8dd2-02fff0c52172
create_collection
hasParameterbeam/3063fb63-164c-4240-8dd2-02fff0c52172
ex:name-parameter
hasParameterbeam/3063fb63-164c-4240-8dd2-02fff0c52172
ex:dimension-parameter
typebeam/b99b8773-86e1-4542-99be-ea39973cacf9
ex:API-Function

References (2)

2 references
  1. ctx:claims/beam/3063fb63-164c-4240-8dd2-02fff0c52172
    • full textbeam-chunk
      text/plain1 KBdoc:beam/3063fb63-164c-4240-8dd2-02fff0c52172
      Show excerpt
      [Turn 1959] Assistant: Designing a retrieval service using a vector database like Milvus is a great choice, especially for handling high-dimensional data and approximate nearest neighbor (ANN) search. Here are some suggestions to improve yo
  2. ctx:claims/beam/b99b8773-86e1-4542-99be-ea39973cacf9
    • full textbeam-chunk
      text/plain1 KBdoc:beam/b99b8773-86e1-4542-99be-ea39973cacf9
      Show excerpt
      If you want to keep the collection dimension at 128, you need to adjust the vectors to have 128 dimensions each. For example: ```python vectors = [ [1.0] * 128, # A vector with 128 elements, all initialized to 1.0 [2.0] * 128 # A

See also

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