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Precision

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-11.)

Precision has 9 facts recorded in Dontopedia across 5 references, with 1 live disagreement.

9 facts·8 predicates·5 sources·1 in dispute

Mostly:computed from(2), rdf:type(1), formula(1)

Maturity scale raw canonical shape-checked rule-derived certified

Computed Fromin disputecomputedFrom

Rdf:typerdf:type

Formulaformula

  • true_positives / expanded_set_size[1]sourceall time · 3601cc0c Ad83 4613 A31f Ab029beb68b6

Calculated incalculatedIn

Rdfs:labelrdfs:label

  • Precision[4]all time · 42448813 8021 446b A5c3 56e15a8d68d9

Is Used tois used to

  • evaluate the model's performance[3]all time · 6de1a07c A949 4280 Bad0 46796da960ac

Is Asserted to Be Greater Than or Equal tois asserted to be greater than or equal to

  • 0.8[2]all time · 309b935e 7e57 44d8 9402 21440414c8d4

Is Calculated Asis calculated as

  • precision_score(true_labels, predictions > 0.5)[2]all time · 309b935e 7e57 44d8 9402 21440414c8d4

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
—
calculatedInbeam/3601cc0c-ad83-4613-a31f-ab029beb68b6
ex:evaluate-relevance
—
computedFrombeam/3601cc0c-ad83-4613-a31f-ab029beb68b6
ex:expanded-set
—
computedFrombeam/3601cc0c-ad83-4613-a31f-ab029beb68b6
ex:true-positives
—
formulabeam/3601cc0c-ad83-4613-a31f-ab029beb68b6
true_positives / expanded_set_size
—
is asserted to be greater than or equal tobeam/309b935e-7e57-44d8-9402-21440414c8d4
0.8
—
is calculated asbeam/309b935e-7e57-44d8-9402-21440414c8d4
precision_score(true_labels, predictions > 0.5)
—
is used tobeam/6de1a07c-a949-4280-bad0-46796da960ac
evaluate the model's performance
—
labelbeam/42448813-8021-446b-a5c3-56e15a8d68d9
Precision
—
typebeam/3f4c4caf-7cac-4379-9d6d-0d4735a709bb
ex:PerformanceMetric

References (5)

5 references
  1. [1]beam-chunk4 facts
    customctx:claims/beam/3601cc0c-ad83-4613-a31f-ab029beb68b6
    • full textbeam-chunk
      text/plain1 KBdoc:beam/3601cc0c-ad83-4613-a31f-ab029beb68b6
      Show excerpt
      Cosine similarity can be used to measure the semantic similarity between the expanded terms and the expected terms, especially if you are using embeddings. ### 4. Intersection Over Union (IoU) IoU is another metric that can be useful, esp…
  2. [2]309b935e 7e57 44d8 9402 21440414c8d42 facts
    customctx:claims/beam/309b935e-7e57-44d8-9402-21440414c8d4
  3. [3]6de1a07c A949 4280 Bad0 46796da960ac1 fact
    customctx:claims/beam/6de1a07c-a949-4280-bad0-46796da960ac
  4. [4]42448813 8021 446b A5c3 56e15a8d68d91 fact
    customctx:claims/beam/42448813-8021-446b-a5c3-56e15a8d68d9
  5. [5]beam-chunk1 fact
    customctx:claims/beam/3f4c4caf-7cac-4379-9d6d-0d4735a709bb
    • full textbeam-chunk
      text/plain1 KBdoc:beam/3f4c4caf-7cac-4379-9d6d-0d4735a709bb
      Show excerpt
      # Output the best combination of weights print(f"Best Intent Precision: {best_precision}") print(f"Best Weights: {best_weights}") ``` ### Explanation 1. **Define Context Components and Initial Weights**: Identify the components of your co…

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