Field Schema Id
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-08.)
Field Schema Id has 10 facts recorded in Dontopedia across 2 references, with 2 live disagreements.
Mostly:rdf:type(2), is primary key(2), field name(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (2)
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.
containsFieldContains Field(1)
- Fields List
ex:fields-list
containsStatementContains Statement(1)
- Code Block
ex:code-block
Other facts (10)
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 | Field Definition | [1] |
| Rdf:type | Field Schema | [2] |
| Is Primary Key | true | [1] |
| Is Primary Key | true | [2] |
| Field Name | id | [1] |
| Field Data Type | Data Type.int64 | [1] |
| Inverse of | Primary Key Field | [1] |
| Has Name | id | [2] |
| Has Data Type | Data Type Int64 | [2] |
| Has Auto Id | true | [2] |
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 (2)
ctx:claims/beam/d4c82979-1650-4b89-a2fa-a0ec5b37bb69- full textbeam-chunktext/plain1 KB
doc:beam/d4c82979-1650-4b89-a2fa-a0ec5b37bb69Show excerpt
FieldSchema(name="id", dtype=DataType.INT64, is_primary=True), FieldSchema(name="vector", dtype=DataType.FLOAT_VECTOR, dim=3) ] schema = CollectionSchema(fields, "RAG Vector Collection") collection = Collection("rag_vectors", schema…
ctx:claims/beam/1c53ac22-55f2-410c-b32e-6b6547174e6f- full textbeam-chunktext/plain1 KB
doc:beam/1c53ac22-55f2-410c-b32e-6b6547174e6fShow excerpt
connections.connect("default", host="localhost", port="19530") # Define the schema fields = [ FieldSchema(name="id", dtype=DataType.INT64, is_primary=True, auto_id=True), FieldSchema(name="embedding", dtype=DataType.FLOAT_VECTOR, d…
See also
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