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Y True

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

Y True has 11 facts recorded in Dontopedia across 4 references, with 2 live disagreements.

11 facts·9 predicates·4 sources·2 in dispute

Mostly:rdf:type(2), intended for(2), represents(1)

Maturity scale raw canonical shape-checked rule-derived certified

Rdf:typein disputerdf:type

Intended forin disputeintendedFor

Representsrepresents

  • ground truth labels[3]sourceall time · 4cc521bd 2791 4334 88dc F5e3519e2d92

Is Extended byisExtendedBy

Extended byextendedBy

Accumulatesaccumulates

Extended WithextendedWith

  • true_vector[1]sourceall time · F008f4ce 021d 4be6 B191 62e598ae1493

Numpy ArraynumpyArray

  • [1, 0, 1, 0][2]all time · 7501fc9d 7281 43a4 B568 1aa8ca61725a

Example ValueexampleValue

  • [1, 0, 1, 0][2]all time · 7501fc9d 7281 43a4 B568 1aa8ca61725a

Inbound mentions (6)

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.

isCalculatedFromIs Calculated From(2)

hasVariableHas Variable(1)

parameterParameter(1)

usedForUsed for(1)

usedInUsed in(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.

11 undated
—
accumulatesbeam/f008f4ce-021d-4be6-b191-62e598ae1493
ex:true_vector
—
exampleValuebeam/7501fc9d-7281-43a4-b568-1aa8ca61725a
[1, 0, 1, 0]
—
extendedBybeam/f008f4ce-021d-4be6-b191-62e598ae1493
ex:true_vector
—
extendedWithbeam/f008f4ce-021d-4be6-b191-62e598ae1493
true_vector
—
intendedForbeam/4cc521bd-2791-4334-88dc-f5e3519e2d92
ex:precision_score
—
intendedForbeam/4cc521bd-2791-4334-88dc-f5e3519e2d92
ex:recall_score
—
isExtendedBybeam/ca2653b8-c25f-4a54-bdfa-ff6ea71f5472
ex:true_vector
—
numpyArraybeam/7501fc9d-7281-43a4-b568-1aa8ca61725a
[1, 0, 1, 0]
—
typebeam/7501fc9d-7281-43a4-b568-1aa8ca61725a
ex:NumpyArray
—
typebeam/f008f4ce-021d-4be6-b191-62e598ae1493
ex:Variable
—
representsbeam/4cc521bd-2791-4334-88dc-f5e3519e2d92
ground truth labels

References (4)

4 references
  1. [1]beam-chunk4 facts
    customctx:claims/beam/f008f4ce-021d-4be6-b191-62e598ae1493
    • full textbeam-chunk
      text/plain1 KBdoc:beam/f008f4ce-021d-4be6-b191-62e598ae1493
      Show excerpt
      dataset = pd.read_csv('queries_dataset.csv') # Split the dataset into training and testing sets train_data, test_data = train_test_split(dataset, test_size=0.2) # Train the RAG system (if needed) # ... # Evaluate the system on the test d…
  2. [2]7501fc9d 7281 43a4 B568 1aa8ca61725a3 facts
    customctx:claims/beam/7501fc9d-7281-43a4-b568-1aa8ca61725a
  3. [3]beam-chunk3 facts
    customctx:claims/beam/4cc521bd-2791-4334-88dc-f5e3519e2d92
    • full textbeam-chunk
      text/plain1 KBdoc:beam/4cc521bd-2791-4334-88dc-f5e3519e2d92
      Show excerpt
      2. **Split the Dataset**: Divide the dataset into training and testing sets. 3. **Evaluate Precision and Recall**: Use precision and recall to evaluate the relevance of the retrieved documents. 4. **User Feedback**: Optionally, collect user…
  4. [4]beam-chunk1 fact
    customctx:claims/beam/ca2653b8-c25f-4a54-bdfa-ff6ea71f5472
    • full textbeam-chunk
      text/plain1 KBdoc:beam/ca2653b8-c25f-4a54-bdfa-ff6ea71f5472
      Show excerpt
      true_vector = [doc in ground_truth_documents for doc in retrieved_documents] pred_vector = [True] * len(retrieved_documents) y_true.extend(true_vector) y_pred.extend(pred_vector) # Calculate precision and recall precision …

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