Dontopedia

Distances

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)

Distances has 5 facts recorded in Dontopedia across 3 references, with 1 live disagreement.

5 facts·2 predicates·3 sources·1 in dispute
Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (4)

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.

printsPrints(1)

printsResultPrints Result(1)

usedForUsed for(1)

usesUses(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:type[1]
Rdf:typeDistance Array[1]
Rdf:typeQuery Result[2]
Formats WithF String[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.

typebeam/9c3d6c77-2b58-4a3b-9618-59e705c00dfd
ex:
typebeam/9c3d6c77-2b58-4a3b-9618-59e705c00dfd
ex:DistanceArray
typebeam/3303e293-04ec-4e6f-bcfd-3af19723cd85
ex:QueryResult
labelbeam/3303e293-04ec-4e6f-bcfd-3af19723cd85
Distances
formatsWithbeam/83decc01-f770-4428-852b-466b97d6139c
ex:f-string

References (3)

3 references
  1. ctx:claims/beam/9c3d6c77-2b58-4a3b-9618-59e705c00dfd
    • full textbeam-chunk
      text/plain1 KBdoc:beam/9c3d6c77-2b58-4a3b-9618-59e705c00dfd
      Show excerpt
      # Normalize the vectors for cosine similarity faiss.normalize_L2(vectors) # Create an IVFPQ index nlist = 100 # Number of clusters m = 8 # Number of subquantizers index = faiss.IndexIVFPQ(faiss.IndexFlatL2(128), 128, nlist, m, 8) # 8 is
  2. ctx:claims/beam/3303e293-04ec-4e6f-bcfd-3af19723cd85
    • full textbeam-chunk
      text/plain1 KBdoc:beam/3303e293-04ec-4e6f-bcfd-3af19723cd85
      Show excerpt
      try: t.save('test.ann') except Exception as e: print(f"Error saving index: {e}") # Load the index from disk try: u = AnnoyIndex(embedding_dim, 'angular') u.load('test.ann') # Load the index except Exception as e: print
  3. ctx:claims/beam/83decc01-f770-4428-852b-466b97d6139c
    • full textbeam-chunk
      text/plain1 KBdoc:beam/83decc01-f770-4428-852b-466b97d6139c
      Show excerpt
      expanded_query = query for lang in languages: if lang != 'en': # Use translation API or model to expand query # For simplicity, we assume a translation function `translate` translated_quer

See also

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