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Vectors to Search

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-08.)

Vectors to Search has 14 facts recorded in Dontopedia across 3 references, with 3 live disagreements.

14 facts·8 predicates·3 sources·3 in dispute

Mostly:contains vector(4), rdf:type(3), contains(2)

Maturity scale raw canonical shape-checked rule-derived certified

Rdf:typein disputerdf:type

  • Array[2]all time · D0aceba9 957f 4351 9d6e 4e00bb1e365c
  • Vector Array[1]sourceall time · D2d5545f 52d7 41f9 8164 91a5b1c460f6
  • Vector Data[3]sourceall time · 845a6907 Ed34 463a 9173 Bf20dfde1501

Contains Vectorin disputecontainsVector

  • Vector 1[2]all time · D0aceba9 957f 4351 9d6e 4e00bb1e365c
  • Vector 2[2]all time · D0aceba9 957f 4351 9d6e 4e00bb1e365c
  • [1.0, 2.0, 3.0][3]sourceall time · 845a6907 Ed34 463a 9173 Bf20dfde1501
  • [4.0, 5.0, 6.0][3]sourceall time · 845a6907 Ed34 463a 9173 Bf20dfde1501

Containsin disputecontains

  • Vector 1[1]sourceall time · D2d5545f 52d7 41f9 8164 91a5b1c460f6
  • Vector 2[1]sourceall time · D2d5545f 52d7 41f9 8164 91a5b1c460f6

Rdfs:labelrdfs:label

  • vectors_to_search[3]sourceall time · 845a6907 Ed34 463a 9173 Bf20dfde1501

Is Array ofis-array-of

  • Vector[2]all time · D0aceba9 957f 4351 9d6e 4e00bb1e365c

Is Used Asis-used-as

Has LengthhasLength

  • 2[2]all time · D0aceba9 957f 4351 9d6e 4e00bb1e365c

Has ValuehasValue

  • [[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]][2]all time · D0aceba9 957f 4351 9d6e 4e00bb1e365c

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.

containsVariableContains Variable(1)

hasValueHas Value(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.

14 undated
—
containsbeam/d2d5545f-52d7-41f9-8164-91a5b1c460f6
ex:vector-1
—
containsbeam/d2d5545f-52d7-41f9-8164-91a5b1c460f6
ex:vector-2
—
containsVectorbeam/d0aceba9-957f-4351-9d6e-4e00bb1e365c
ex:vector-1
—
containsVectorbeam/d0aceba9-957f-4351-9d6e-4e00bb1e365c
ex:vector-2
—
containsVectorbeam/845a6907-ed34-463a-9173-bf20dfde1501
[1.0, 2.0, 3.0]
—
containsVectorbeam/845a6907-ed34-463a-9173-bf20dfde1501
[4.0, 5.0, 6.0]
—
hasLengthbeam/d0aceba9-957f-4351-9d6e-4e00bb1e365c
2
—
hasValuebeam/d0aceba9-957f-4351-9d6e-4e00bb1e365c
[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]
—
is-array-ofbeam/d0aceba9-957f-4351-9d6e-4e00bb1e365c
ex:vector
—
is-used-asbeam/d0aceba9-957f-4351-9d6e-4e00bb1e365c
ex:search-data
—
labelbeam/845a6907-ed34-463a-9173-bf20dfde1501
vectors_to_search
—
typebeam/d0aceba9-957f-4351-9d6e-4e00bb1e365c
ex:Array
—
typebeam/d2d5545f-52d7-41f9-8164-91a5b1c460f6
ex:VectorArray
—
typebeam/845a6907-ed34-463a-9173-bf20dfde1501
ex:VectorData

References (3)

3 references
  1. [1]beam-chunk3 facts
    customctx:claims/beam/d2d5545f-52d7-41f9-8164-91a5b1c460f6
    • full textbeam-chunk
      text/plain1 KBdoc:beam/d2d5545f-52d7-41f9-8164-91a5b1c460f6
      Show excerpt
      By following these guidelines, you should be able to set up a Milvus cluster that meets your requirements for high availability and performance. [Turn 4916] User: I'm working on optimizing the performance of my Milvus cluster, and I want t…
  2. [2]D0aceba9 957f 4351 9d6e 4e00bb1e365c7 facts
    customctx:claims/beam/d0aceba9-957f-4351-9d6e-4e00bb1e365c
  3. [3]beam-chunk4 facts
    customctx:claims/beam/845a6907-ed34-463a-9173-bf20dfde1501
    • full textbeam-chunk
      text/plain1 KBdoc:beam/845a6907-ed34-463a-9173-bf20dfde1501
      Show excerpt
      FieldSchema(name="id", dtype=DataType.INT64, is_primary=True, auto_id=True), FieldSchema(name="embedding", dtype=DataType.FLOAT_VECTOR, dim=128) ] schema = CollectionSchema(fields, "Test Collection") # Create a collection collectio…

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