ML Metadata
E1338342
UNEXPLORED
ML Metadata is a library for recording, tracking, and querying metadata about machine learning workflows, artifacts, and experiments.
All labels observed (2)
| Label | Occurrences |
|---|---|
| ML Metadata canonical | 2 |
| ML Metadata store | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T18704799 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ML Metadata Context triple: [TFX, includesLibrary, ML Metadata]
-
A.
S-100 metadata framework
The S-100 metadata framework is an IHO-developed standard that defines a flexible, interoperable structure for describing and managing geospatial and hydrographic data within the broader S-100 universal hydrographic data model.
-
B.
METS
METS (Metadata Encoding and Transmission Standard) is an XML-based standard for encoding descriptive, administrative, and structural metadata for complex digital library objects.
-
C.
MODS (Metadata Object Description Schema)
MODS (Metadata Object Description Schema) is an XML-based bibliographic description standard designed to provide a flexible, user-friendly alternative to MARC for describing and sharing library and cultural heritage resources.
-
D.
DataCite metadata schema
The DataCite metadata schema is a widely used standard for describing research datasets and other scholarly outputs to support citation, discovery, and persistent identification.
-
E.
MADS (Metadata Authority Description Schema)
MADS (Metadata Authority Description Schema) is an XML-based schema used primarily by libraries and related institutions to structure and manage authority data for names, subjects, and other controlled vocabularies.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ML Metadata Target entity description: ML Metadata is a library for recording, tracking, and querying metadata about machine learning workflows, artifacts, and experiments.
-
A.
S-100 metadata framework
The S-100 metadata framework is an IHO-developed standard that defines a flexible, interoperable structure for describing and managing geospatial and hydrographic data within the broader S-100 universal hydrographic data model.
-
B.
METS
METS (Metadata Encoding and Transmission Standard) is an XML-based standard for encoding descriptive, administrative, and structural metadata for complex digital library objects.
-
C.
MODS (Metadata Object Description Schema)
MODS (Metadata Object Description Schema) is an XML-based bibliographic description standard designed to provide a flexible, user-friendly alternative to MARC for describing and sharing library and cultural heritage resources.
-
D.
DataCite metadata schema
The DataCite metadata schema is a widely used standard for describing research datasets and other scholarly outputs to support citation, discovery, and persistent identification.
-
E.
MADS (Metadata Authority Description Schema)
MADS (Metadata Authority Description Schema) is an XML-based schema used primarily by libraries and related institutions to structure and manage authority data for names, subjects, and other controlled vocabularies.
- F. None of above. chosen
Referenced by (3)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: ML Metadata