Dontopedia

Search Config

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

Search Config has 9 facts recorded in Dontopedia across 3 references.

9 facts·9 predicates·3 sources

Mostly:has mode(1), has depth(1), has format(1)

Maturity scale raw canonical shape-checked rule-derived certified

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
PredicateValueRef
Has Modedefault (with cache)[1]
Has Depth2[1]
Has Formatdefault[1]
Specifies MetricL2-distance[2]
Specifies Top K10[2]
Rdf:typeParameter Configuration[3]
Has Nprobe Value10[3]
Has Limit Value10[3]
Applied toSearch Operation[3]

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.

9 undated
—
hasModeblah/omega/part-1011
default (with cache)
—
hasDepthblah/omega/part-1011
2
—
hasFormatblah/omega/part-1011
default
—
specifiesMetricbeam/7da0d616-0de7-4880-bacb-4a0a15c5a9c9
L2-distance
—
specifiesTopKbeam/7da0d616-0de7-4880-bacb-4a0a15c5a9c9
10
—
typebeam/c92eb763-b9ec-407a-a291-c2cb3a0f17b8
ex:ParameterConfiguration
—
hasNprobeValuebeam/c92eb763-b9ec-407a-a291-c2cb3a0f17b8
10
—
hasLimitValuebeam/c92eb763-b9ec-407a-a291-c2cb3a0f17b8
10
—
appliedTobeam/c92eb763-b9ec-407a-a291-c2cb3a0f17b8
ex:search-operation

References (3)

3 references
  1. [1]Part 10113 facts
    ctx:discord/blah/omega/part-1011
  2. [2]7da0d616 0de7 4880 Bacb 4a0a15c5a9c92 facts
    ctx:claims/beam/7da0d616-0de7-4880-bacb-4a0a15c5a9c9
    • full textbeam-chunk
      text/plain1 KBdoc:beam/7da0d616-0de7-4880-bacb-4a0a15c5a9c9
      Show excerpt
      vectors = np.random.rand(num_vectors, 128).astype('float32').tolist() ids = [str(i) for i in range(num_vectors)] self.collection.insert(vectors, ids) query_vector = np.random.rand(1, 128).asty…
  3. [3]C92eb763 B9ec 407a A291 C2cb3a0f17b84 facts
    ctx:claims/beam/c92eb763-b9ec-407a-a291-c2cb3a0f17b8
    • full textbeam-chunk
      text/plain1 KBdoc:beam/c92eb763-b9ec-407a-a291-c2cb3a0f17b8
      Show excerpt
      vectors = np.random.rand(1000, 128).astype(np.float32) collection.insert([vectors]) # Flush data collection.flush() # Search query_vector = np.random.rand(1, 128).astype(np.float32) results = collection.search([query_vector], "embedding",…

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