Batch Search Function
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-08.)
Batch Search Function has 19 facts recorded in Dontopedia across 1 reference, with 2 live disagreements.
Mostly:parameter(2), uses(2), rdf:type(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound 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.
callsCalls(1)
- Test Section
ex:test-section
demonstratesDemonstrates(1)
- Test Section
ex:test-section
isUsedByIs Used by(1)
- Thread Pool Executor
ex:thread-pool-executor
performedInPerformed in(1)
- Result Extension
ex:result-extension
usedInUsed in(1)
- Array Split
ex:array-split
verifiesVerifies(1)
- Test Section
ex:test-section
Other facts (19)
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 |
|---|---|---|
| Parameter | query_vectors | [1] |
| Parameter | batch_size | [1] |
| Uses | Thread Pool Executor | [1] |
| Uses | Futures Pattern | [1] |
| Rdf:type | Python Function | [1] |
| Default Batch Size | 1000 | [1] |
| Processing Mode | multi-threading | [1] |
| Splits | query vectors | [1] |
| Result Component | Search Results | [1] |
| Initializes | Results List | [1] |
| Creates | Futures List | [1] |
| Iterates | Futures List | [1] |
| Returns | Results List | [1] |
| Calls | Search Vectors Function | [1] |
| Splits by | batch_size | [1] |
| Uses List Comprehension | futures creation | [1] |
| Processes in Batches | Query Vectors | [1] |
| Submits Per Batch | multiple search tasks | [1] |
| Collects Results | Results List | [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/5a92a7f8-dbf8-4e2c-bec0-f0a72a9230c9- full textbeam-chunktext/plain1 KB
doc:beam/5a92a7f8-dbf8-4e2c-bec0-f0a72a9230c9Show excerpt
from concurrent.futures import ThreadPoolExecutor # Create a FAISS index d = 128 # dimension index = faiss.IndexFlatL2(d) # Add vectors to the index vectors = np.random.rand(10000, d).astype('float32') index.add(vectors) # Function to p…
See also
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