Prepare Training Data
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)
Prepare Training Data has 6 facts recorded in Dontopedia across 1 reference, with 1 live disagreement.
Mostly:contains(2), rdf:type(1), precedes(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (3)
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.
containsContains(1)
- Explanation Section
explanation-section
dependencyForDependency for(1)
- Split Data
ex:split-data
precedesPrecedes(1)
- Split Data
ex:split-data
Other facts (6)
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.
| Predicate | Value | Ref |
|---|---|---|
| Contains | Convert to Tokenized List | [1] |
| Contains | Initialize Bm25 | [1] |
| Rdf:type | Step | [1] |
| Precedes | Predict Labels | [1] |
| Depends on | Split Data | [1] |
| Step Number | 3 | [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.
References (1)
ctx:claims/beam/9669963d-f7d7-452d-a9ec-0cf09ed6be1d- full textbeam-chunktext/plain1 KB
doc:beam/9669963d-f7d7-452d-a9ec-0cf09ed6be1dShow excerpt
predictions.append(predicted_label) return predictions # Make predictions predictions = predict_labels(test_df, bm25, train_df) # Calculate the recall score recall = recall_score(test_df['label'], predictions, average='binary'…
See also
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