Query Vector 128
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-06.)
Query Vector 128 has 10 facts recorded in Dontopedia across 3 references, with 2 live disagreements.
Mostly:rdf:type(3), constructed from(2), vector size(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.
hasValueHas Value(2)
- Near Vector Object
ex:near-vector-object - Near Vector Param
ex:near-vector-param
usesQueryVectorUses Query Vector(2)
- Vector Search
ex:vector-search - Vector Search Example
ex:vector-search-example
Other facts (9)
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 | Vector | [1] |
| Rdf:type | Query Variable | [2] |
| Rdf:type | Vector | [3] |
| Constructed From | Repeated Sequence | [1] |
| Constructed From | [0.1, 0.2, 0.3, 0.4] repeated 32 times | [3] |
| Vector Size | 128 | [1] |
| Assigned to | Near Vector 128 | [2] |
| Has Size | 128 | [3] |
| Uses Technique | Vector Repetition | [3] |
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 (3)
ctx:claims/beam/f80d8de8-0d2a-446e-ac9c-fc4672dce4f0- full textbeam-chunktext/plain1 KB
doc:beam/f80d8de8-0d2a-446e-ac9c-fc4672dce4f0Show excerpt
# Create the schema in Weaviate client.schema.create_class(schema) print("Schema created successfully.") ``` #### Inserting Data When inserting data, you can specify which vector property to use based on the vector size. ```python # Add …
ctx:claims/beam/df58a3ab-2df5-43d0-a3c7-d866e2d0138c- full textbeam-chunktext/plain1 KB
doc:beam/df58a3ab-2df5-43d0-a3c7-d866e2d0138cShow excerpt
.with_near_vector(near_vector_128) .with_limit(10) .do() ) print("Vector search query successful (size 128):") print(result_128) query_vector_256 = [0.5, 0.6, 0.7, 0.8] * 64 # Example query vector of size 256 near_vector_256 …
ctx:claims/beam/ea34a816-3421-425e-97a9-50206b2c6248
See also
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