Dontopedia
Explore

Faiss Index

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

Faiss Index has 11 facts recorded in Dontopedia across 3 references, with 1 live disagreement.

11 facts·10 predicates·3 sources·1 in dispute

Mostly:invokes(2), metric(1), rdf:type(1)

Maturity scale raw canonical shape-checked rule-derived certified

Invokesin disputeinvokes

Metricmetric

  • L2[2]sourceall time · F3d5dce4 0492 435e 9a07 8eec7bd68f9b

Rdf:typerdf:type

  • Index[2]sourceall time · F3d5dce4 0492 435e 9a07 8eec7bd68f9b

Rdfs:labelrdfs:label

  • FAISS Index[1]all time · 8928fff6 028a 4c31 9801 9484b10c9c03

Has Codehas-code

  • 8[1]sourceall time · 8928fff6 028a 4c31 9801 9484b10c9c03

Has Mhas-m

  • 8[1]sourceall time · 8928fff6 028a 4c31 9801 9484b10c9c03

Has Nlisthas-nlist

  • 100[1]sourceall time · 8928fff6 028a 4c31 9801 9484b10c9c03

Has Dimensionhas-dimension

  • 128[1]sourceall time · 8928fff6 028a 4c31 9801 9484b10c9c03

Uses Metricuses-metric

  • L2 Metric[1]sourceall time · 8928fff6 028a 4c31 9801 9484b10c9c03

Supports AlgorithmssupportsAlgorithms

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.

11 undated
—
has-codebeam/8928fff6-028a-4c31-9801-9484b10c9c03
8
—
has-dimensionbeam/8928fff6-028a-4c31-9801-9484b10c9c03
128
—
has-mbeam/8928fff6-028a-4c31-9801-9484b10c9c03
8
—
has-nlistbeam/8928fff6-028a-4c31-9801-9484b10c9c03
100
—
invokesbeam/8928fff6-028a-4c31-9801-9484b10c9c03
ex:add-method
—
invokesbeam/8928fff6-028a-4c31-9801-9484b10c9c03
ex:search-method
—
metricbeam/f3d5dce4-0492-435e-9a07-8eec7bd68f9b
L2
—
labelbeam/8928fff6-028a-4c31-9801-9484b10c9c03
FAISS Index
—
typebeam/f3d5dce4-0492-435e-9a07-8eec7bd68f9b
ex:Index
—
supportsAlgorithmsbeam/6ec3a2c8-a4c5-4d8f-b39a-c00b8aac8e2c
ex:ivfpq-algorithm
—
uses-metricbeam/8928fff6-028a-4c31-9801-9484b10c9c03
ex:L2-metric

References (3)

3 references
  1. [1]beam-chunk8 facts
    customctx:claims/beam/8928fff6-028a-4c31-9801-9484b10c9c03
    • full textbeam-chunk
      text/plain1 KBdoc:beam/8928fff6-028a-4c31-9801-9484b10c9c03
      Show excerpt
      To further optimize the query time, you can adjust the parameters: - **`nlist`**: Increasing `nlist` can improve accuracy but may increase memory usage and query time. - **`m`**: The number of subquantizers affects the trade-off between sp…
  2. [2]beam-chunk2 facts
    customctx:claims/beam/f3d5dce4-0492-435e-9a07-8eec7bd68f9b
    • full textbeam-chunk
      text/plain1 KBdoc:beam/f3d5dce4-0492-435e-9a07-8eec7bd68f9b
      Show excerpt
      print(f"Processing dense query: {query_vector}") _, I = self.index.search(query_vector, k=10) return [f"dense_result_{i}" for i in I[0]] # Initialize FAISS index d = 128 # dimension n = 8000 # number of vectors np…
  3. [3]6ec3a2c8 A4c5 4d8f B39a C00b8aac8e2c1 fact
    customctx:claims/beam/6ec3a2c8-a4c5-4d8f-b39a-c00b8aac8e2c

See also

Keep researching

Missing something or suspicious of what's here? Kick off a research session — a Claude agent will investigate, cite its sources, and file new facts into a dedicated context you can review before accepting into the shared view.

↑