Dontopedia

ground truth

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)

ground truth has 4 facts recorded in Dontopedia across 2 references, with 1 live disagreement.

4 facts·2 predicates·2 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.

hasParameterHas Parameter(2)

compares-withCompares With(1)

takesParameterTakes Parameter(1)

Other facts (3)

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.

3 facts
PredicateValueRef
Rdf:typeFunction Parameter[1]
Rdf:typeReference Data[2]
Used forAccuracy Comparison[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.

typebeam/2f563017-4d59-46fb-86fd-983fcce6598f
ex:FunctionParameter
usedForbeam/2f563017-4d59-46fb-86fd-983fcce6598f
ex:accuracy-comparison
typebeam/f85640f6-6171-48b4-a25c-15c083b59052
ex:ReferenceData
labelbeam/f85640f6-6171-48b4-a25c-15c083b59052
ground truth

References (2)

2 references
  1. ctx:claims/beam/2f563017-4d59-46fb-86fd-983fcce6598f
    • full textbeam-chunk
      text/plain1 KBdoc:beam/2f563017-4d59-46fb-86fd-983fcce6598f
      Show excerpt
      ### 4. Use Ground Truth Data Having a set of documents with known metadata can help you evaluate and improve the accuracy of Tika's metadata extraction. ### Example Code Here's an example of how you can preprocess the documents, extract m
  2. ctx:claims/beam/f85640f6-6171-48b4-a25c-15c083b59052
    • full textbeam-chunk
      text/plain1 KBdoc:beam/f85640f6-6171-48b4-a25c-15c083b59052
      Show excerpt
      print(f"Best Threshold: {best_threshold}, Best Accuracy: {best_accuracy}") # Tune the queries with the best threshold tuned_queries = tune_thresholds(queries, best_threshold) print(tuned_queries) ``` ### Explanation 1. **Cross-Validation

See also

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