collection
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)
collection has 7 facts recorded in Dontopedia across 3 references, with 2 live disagreements.
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (8)
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.
isCalledOnIs Called on(5)
- Create Index Method
ex:create-index-method - Describe Index Method
ex:describe-index-method - Index Drop Method
ex:index-drop-method - Insert Method
ex:insert-method - Search Method
ex:search-method
assignsVariableAssigns Variable(1)
- Step Create Collection
ex:step-create-collection
createsCollectionCreates Collection(1)
- Corrected Code Solution 2
ex:corrected-code-solution-2
isInstantiatedAsIs Instantiated As(1)
- Collection Class
ex:collection-class
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 |
|---|---|---|
| Rdf:type | String Variable | [1] |
| Rdf:type | Collection | [2] |
| Rdf:type | Collection Instance | [3] |
| Has Attribute Name | name | [3] |
| Has Attribute Name | schema | [3] |
| Is Initialized With | Collection Class | [3] |
Timeline
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References (3)
ctx:claims/beam/b99b8773-86e1-4542-99be-ea39973cacf9- full textbeam-chunktext/plain1 KB
doc:beam/b99b8773-86e1-4542-99be-ea39973cacf9Show excerpt
If you want to keep the collection dimension at 128, you need to adjust the vectors to have 128 dimensions each. For example: ```python vectors = [ [1.0] * 128, # A vector with 128 elements, all initialized to 1.0 [2.0] * 128 # A…
ctx:claims/beam/c1884d4f-6cc0-42a1-9d04-1b18cb1f2a49- full textbeam-chunktext/plain1 KB
doc:beam/c1884d4f-6cc0-42a1-9d04-1b18cb1f2a49Show excerpt
# Connect to Milvus server connections.connect("default", host="localhost", port="19530") # Define schema fields = [ FieldSchema(name="id", dtype=DataType.INT64, is_primary=True), FieldSchema(name="vector", dtype=DataType.FLOAT_VEC…
ctx:claims/beam/97be8b15-c3b6-4489-b398-6a37a9bde5f9- full textbeam-chunktext/plain1 KB
doc:beam/97be8b15-c3b6-4489-b398-6a37a9bde5f9Show excerpt
collection_name = "my_collection" collection = Collection(name=collection_name, schema=schema) # Check if the index is built index_info = collection.describe_index() if index_info["params"] == {}: print("Index not built. Rebuilding the…
See also
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