search
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)
search has 10 facts recorded in Dontopedia across 4 references, with 3 live disagreements.
Mostly:rdf:type(4), has value(2), value type(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound 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.
containsContains(1)
- Input Key
ex:input-key
hasKeyHas Key(1)
- Engine
ex:engine
hasKeyValueHas Key Value(1)
- Engine Dictionary
ex:engine-dictionary
usesSurnameMatchesAsUses Surname Matches As(1)
- Paternal Pedigree Testimony 2026 06 09
ex:paternal-pedigree-testimony-2026-06-09
Other facts (8)
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 |
|---|---|---|
| Rdf:type | Function Key | [1] |
| Rdf:type | Dictionary Key | [2] |
| Rdf:type | Dictionary Key | [3] |
| Rdf:type | Json Key | [4] |
| Has Value | Search Lambda | [1] |
| Has Value | Lambda Function | [2] |
| Value Type | Json Object | [4] |
| Contains | Request Key | [4] |
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 (4)
ctx:claims/beam/3d2ebcc2-edde-456b-8a3a-1cb1f7bd0026- full textbeam-chunktext/plain1 KB
doc:beam/3d2ebcc2-edde-456b-8a3a-1cb1f7bd0026Show excerpt
# Example usage engine = { 'search': lambda x: np.random.choice([0, 1], size=x.shape[0]) } metrics = test_sparse_retrieval_engine(engine) print(f"Average Duration: {metrics['average_duration']:.4f} seconds") print(f"Average Throughput: …
ctx:claims/beam/059dfa3d-8d94-4bfc-bbe2-1c2228c8c6fe- full textbeam-chunktext/plain1 KB
doc:beam/059dfa3d-8d94-4bfc-bbe2-1c2228c8c6feShow excerpt
total_duration += timer.duration total_throughput += num_queries / timer.duration latencies.append(timer.duration) # Assuming results is a binary array indicating relevance precision = precision_scor…
ctx:claims/beam/93399bbc-ebe1-4c6b-be2c-c95de6e77fa8ctx:claims/beam/670e056f-4c4f-44c8-a6bd-86fd66ec1102
See also
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