Triple
T18704799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TFX |
E457341
|
entity |
| Predicate | includesLibrary |
P1393
|
FINISHED |
| Object | ML Metadata |
—
|
NE NERFINISHED |
How this triple was built (3 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: ML Metadata | Statement: [TFX, includesLibrary, ML Metadata]
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
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5671665bc8190b9b4a4ce4ec5b2eb |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 10, 2026, 11:49 a.m.