embedding

as donto believed on

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-11.)

embedding has 40 facts recorded in Dontopedia across 9 references, with 4 live disagreements.

40 facts·18 predicates·9 sources·4 in dispute

Mostly:rdf:type(8), has data type(5), dimension(4)

Inbound mentions (30)

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.

`hasField`Has Field(7)

Collection Schemacollection-schema
Collection Schemaex:collection-schema
Document Embeddings Schemaex:document-embeddings-schema
Example Schemaex:example-schema
My Collection Schemaex:my-collection-schema
Schemaex:schema
Schema Definitionex:schema-definition

`contains`Contains(3)

Field Listex:field-list
Fields Arrayex:fields-array
Fields Listex:fields-list

`containsField`Contains Field(2)

Fieldsex:fields
My Collection Schemaex:my-collection-schema

`definesField`Defines Field(2)

Schema Definitionex:schema-definition
Setup Milvus Pyex:setup-milvus-py

`searchesField`Searches Field(2)

Search Operationex:search-operation
Similarity Searchex:similarity-search

`appliedToField`Applied to Field(1)

Index Paramsex:index-params

`containsEntity`Contains Entity(1)

Fields Variableex:fields-variable

`createdOn`Created on(1)

Indexex:index

`createdOnField`Created on Field(1)

Embedding Indexex:embedding-index

`defines`Defines(1)

Field Schemaex:field-schema

`hasPart`Has Part(1)

Example Schemaex:example-schema

`instantiates`Instantiates(1)

Field SchemaFieldSchema

`instantiatesFieldSchema`Instantiates Field Schema(1)

Setup Milvus Pyex:setup-milvus-py

`member`Member(1)

Fields Variableex:fields-variable

`operates-on`Operates on(1)

Searchex:search

`specifies`Specifies(1)

Anns Field Argumentex:anns-field-argument

`targetField`Target Field(1)

Index Creationex:index-creation

`targetsField`Targets Field(1)

Index Creationex:index-creation

`usedFor`Used for(1)

Index Paramsex:index-params

Other facts (35)

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.

35 facts

Predicate	Value	Ref
Rdf:type	Field Schema	[1]
Rdf:type	Field	[2]
Rdf:type	Field Definition	[3]
Rdf:type	Field	[4]
Rdf:type	Field	[5]
Rdf:type	Field Schema	[6]
Rdf:type	Field Schema	[7]
Rdf:type	Field	[9]
Has Data Type	Float Vector	[2]
Has Data Type	Float Vector	[4]
Has Data Type	DataType.FLOAT_VECTOR	[4]
Has Data Type	Data Type Float Vector	[5]
Has Data Type	Float Vector Data Type	[8]
Dimension	128	[1]
Dimension	128	[2]
Dimension	128	[6]
Dimension	128	[7]
Has Dimension	128	[2]
Has Dimension	128	[4]
Has Dimension	128	[8]
Dtype	FLOAT_VECTOR	[1]
Dtype	Float Vector	[2]
Field Name	embedding	[3]
Field Data Type	FLOAT_VECTOR	[3]
Vector Dimension	128	[3]
Has Name	embedding	[4]
Requires Dimension	128	[4]
Serves As	Vector Column	[4]
Inverse Has Field	Collection Schema	[5]
Data Type	FLOAT_VECTOR	[6]
Is Vector	true	[6]
Data Type	FLOAT_VECTOR	[7]
Is Vector Dimension	128	[7]
Part of	Example Schema	[8]
Has Attribute	Dimension Attribute	[8]

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.

40 undated

—

dtypebeam/58af948e-ad4f-4c4d-8464-06c37433c965

FLOAT_VECTOR

—

dimensionbeam/58af948e-ad4f-4c4d-8464-06c37433c965

128

—

typebeam/58af948e-ad4f-4c4d-8464-06c37433c965

ex:FieldSchema

—

labelbeam/58af948e-ad4f-4c4d-8464-06c37433c965

embedding

—

typebeam/bf38e99d-74ad-46c4-a6f9-80d36566aa7b

ex:Field

—

labelbeam/bf38e99d-74ad-46c4-a6f9-80d36566aa7b

embedding

—

dtypebeam/bf38e99d-74ad-46c4-a6f9-80d36566aa7b

ex:FLOAT_VECTOR

—

dimensionbeam/bf38e99d-74ad-46c4-a6f9-80d36566aa7b

128

—

hasDimensionbeam/bf38e99d-74ad-46c4-a6f9-80d36566aa7b

128

—

hasDataTypebeam/bf38e99d-74ad-46c4-a6f9-80d36566aa7b

ex:FLOAT_VECTOR

—

typebeam/1e47faff-9001-4475-b47f-aee14dcc46af

ex:FieldDefinition

—

fieldNamebeam/1e47faff-9001-4475-b47f-aee14dcc46af

embedding

—

fieldDataTypebeam/1e47faff-9001-4475-b47f-aee14dcc46af

FLOAT_VECTOR

—

vectorDimensionbeam/1e47faff-9001-4475-b47f-aee14dcc46af

128

—

typebeam/86785515-9f1f-4fdd-887b-9264324ad027

ex:Field

—

hasNamebeam/86785515-9f1f-4fdd-887b-9264324ad027

embedding

—

hasDataTypebeam/86785515-9f1f-4fdd-887b-9264324ad027

ex:FLOAT_VECTOR

—

hasDimensionbeam/86785515-9f1f-4fdd-887b-9264324ad027

128

—

requiresDimensionbeam/86785515-9f1f-4fdd-887b-9264324ad027

128

—

servesAsbeam/86785515-9f1f-4fdd-887b-9264324ad027

ex:vector-column

—

hasDataTypebeam/86785515-9f1f-4fdd-887b-9264324ad027

DataType.FLOAT_VECTOR

—

typebeam/1c53ac22-55f2-410c-b32e-6b6547174e6f

ex:Field

—

labelbeam/1c53ac22-55f2-410c-b32e-6b6547174e6f

embedding

—

inverseHasFieldbeam/1c53ac22-55f2-410c-b32e-6b6547174e6f

ex:collection-schema

—

hasDataTypebeam/1c53ac22-55f2-410c-b32e-6b6547174e6f

ex:data-type-float-vector

—

typebeam/845a6907-ed34-463a-9173-bf20dfde1501

ex:FieldSchema

—

labelbeam/845a6907-ed34-463a-9173-bf20dfde1501

embedding

—

data-typebeam/845a6907-ed34-463a-9173-bf20dfde1501

FLOAT_VECTOR

—

dimensionbeam/845a6907-ed34-463a-9173-bf20dfde1501

128

—

isVectorbeam/845a6907-ed34-463a-9173-bf20dfde1501

true

—

typebeam/eaf4690f-b473-4ddb-a331-5a3e658a880c

ex:FieldSchema

—

namebeam/eaf4690f-b473-4ddb-a331-5a3e658a880c

embedding

—

dataTypebeam/eaf4690f-b473-4ddb-a331-5a3e658a880c

FLOAT_VECTOR

—

dimensionbeam/eaf4690f-b473-4ddb-a331-5a3e658a880c

128

—

isVectorDimensionbeam/eaf4690f-b473-4ddb-a331-5a3e658a880c

128

—

hasDataTypebeam/886e5d26-dd7f-4315-aed0-e67c69b9eb2f

ex:float-vector-data-type

—

hasDimensionbeam/886e5d26-dd7f-4315-aed0-e67c69b9eb2f

128

—

partOfbeam/886e5d26-dd7f-4315-aed0-e67c69b9eb2f

ex:example-schema

—

hasAttributebeam/886e5d26-dd7f-4315-aed0-e67c69b9eb2f

ex:dimension-attribute

—

typebeam/3ec8c303-e081-4923-9f67-5956a4f6bef5

ex:Field

References (9)

9 references

[1]58af948e Ad4f 4c4d 8464 06c37433c9654 facts
ctx:claims/beam/58af948e-ad4f-4c4d-8464-06c37433c965
- full textbeam-chunk
  text/plain1 KBdoc:beam/58af948e-ad4f-4c4d-8464-06c37433c965
  Show excerpt
  import numpy as np from pymilvus import connections, FieldSchema, CollectionSchema, DataType, Collection, utility # Initialize Milvus connections.connect("default", host="localhost", port="19530") # Define schema fields = [ FieldSchem…
[2]Bf38e99d 74ad 46c4 A6f9 80d36566aa7b6 facts
ctx:claims/beam/bf38e99d-74ad-46c4-a6f9-80d36566aa7b
- full textbeam-chunk
  text/plain1 KBdoc:beam/bf38e99d-74ad-46c4-a6f9-80d36566aa7b
  Show excerpt
  - **Disaster Recovery**: Have a disaster recovery plan in place to quickly recover from failures. ### 8. **Security** - **Authentication and Authorization**: Implement authentication and authorization mechanisms to secure access to your Mi…
[3]1e47faff 9001 4475 B47f Aee14dcc46af4 facts
ctx:claims/beam/1e47faff-9001-4475-b47f-aee14dcc46af
- full textbeam-chunk
  text/plain1 KBdoc:beam/1e47faff-9001-4475-b47f-aee14dcc46af
  Show excerpt
  Create a Python script named `setup_milvus.py` with the following content: ```python from pymilvus import connections, FieldSchema, CollectionSchema, DataType, Collection # Connect to Milvus connections.connect("default", ho…
[4]86785515 9f1f 4fdd 887b 9264324ad0277 facts
ctx:claims/beam/86785515-9f1f-4fdd-887b-9264324ad027
[5]1c53ac22 55f2 410c B32e 6b6547174e6f4 facts
ctx:claims/beam/1c53ac22-55f2-410c-b32e-6b6547174e6f
- full textbeam-chunk
  text/plain1 KBdoc:beam/1c53ac22-55f2-410c-b32e-6b6547174e6f
  Show 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…
[6]845a6907 Ed34 463a 9173 Bf20dfde15015 facts
ctx:claims/beam/845a6907-ed34-463a-9173-bf20dfde1501
- full textbeam-chunk
  text/plain1 KBdoc:beam/845a6907-ed34-463a-9173-bf20dfde1501
  Show excerpt
  FieldSchema(name="id", dtype=DataType.INT64, is_primary=True, auto_id=True), FieldSchema(name="embedding", dtype=DataType.FLOAT_VECTOR, dim=128) ] schema = CollectionSchema(fields, "Test Collection") # Create a collection collectio…
[7]Eaf4690f B473 4ddb A331 5a3e658a880c5 facts
ctx:claims/beam/eaf4690f-b473-4ddb-a331-5a3e658a880c
- full textbeam-chunk
  text/plain1 KBdoc:beam/eaf4690f-b473-4ddb-a331-5a3e658a880c
  Show excerpt
```python from pymilvus import connections, FieldSchema, CollectionSchema, DataType, Collection import numpy as np # Connect to Milvus connections.connect("default", host="localhost", port="19530") # Define the schema fields = [ Field…
[8]886e5d26 Dd7f 4315 Aed0 E67c69b9eb2f4 facts
ctx:claims/beam/886e5d26-dd7f-4315-aed0-e67c69b9eb2f
- full textbeam-chunk
  text/plain1 KBdoc:beam/886e5d26-dd7f-4315-aed0-e67c69b9eb2f
  Show excerpt
  Ensure that the index creation process has completed successfully. You can check the status of the index building process using the `describe_index` method. 2. **Rebuild the Index**: If the index is not built, you may need to rebuild…
[9]3ec8c303 E081 4923 9f67 5956a4f6bef51 fact
ctx:claims/beam/3ec8c303-e081-4923-9f67-5956a4f6bef5

Keep researching

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embedding

Inbound mentions (30)

hasFieldHas Field(7)

containsContains(3)

containsFieldContains Field(2)

definesFieldDefines Field(2)

searchesFieldSearches Field(2)

appliedToFieldApplied to Field(1)

containsEntityContains Entity(1)

createdOnCreated on(1)

createdOnFieldCreated on Field(1)

definesDefines(1)

hasPartHas Part(1)

instantiatesInstantiates(1)

instantiatesFieldSchemaInstantiates Field Schema(1)

memberMember(1)

operates-onOperates on(1)

specifiesSpecifies(1)

targetFieldTarget Field(1)

targetsFieldTargets Field(1)

usedForUsed for(1)

Other facts (35)

Timeline

References (9)

See also

Keep researching

`hasField`Has Field(7)

`contains`Contains(3)

`containsField`Contains Field(2)

`definesField`Defines Field(2)

`searchesField`Searches Field(2)

`appliedToField`Applied to Field(1)

`containsEntity`Contains Entity(1)

`createdOn`Created on(1)

`createdOnField`Created on Field(1)

`defines`Defines(1)

`hasPart`Has Part(1)

`instantiates`Instantiates(1)

`instantiatesFieldSchema`Instantiates Field Schema(1)

`member`Member(1)

`operates-on`Operates on(1)

`specifies`Specifies(1)

`targetField`Target Field(1)

`targetsField`Targets Field(1)

`usedFor`Used for(1)