Triple
T6825048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Master of Fine Arts |
E156993
|
entity |
| Predicate | typicalDiscipline |
P25609
|
FINISHED |
| Object | visual arts |
—
|
LITERAL FINISHED |
How this triple was built (2 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: visual arts | Statement: [Master of Fine Arts, typicalDiscipline, visual arts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDiscipline Context triple: [Master of Fine Arts, typicalDiscipline, visual arts]
-
A.
governingDiscipline
Indicates that one discipline or field provides the primary rules, principles, or framework that regulate or guide another activity, domain, or practice.
-
B.
typeDiscipline
chosen
Indicates that an entity is associated with, categorized under, or characterized by a particular discipline or field of study.
-
C.
featuredDiscipline
Indicates that one discipline is highlighted or given special prominence in relation to another entity or context.
-
D.
associatedWithDiscipline
Indicates that an entity has a relevant connection or involvement with a particular academic, professional, or thematic discipline.
-
E.
supportsDiscipline
Indicates that one entity provides assistance, resources, or endorsement that helps sustain or advance a particular discipline.
- F. None of above.
Provenance (3 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_69c6882a5b5c8190917a7db9ed36bad1 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d581ea5881908ba78c6bf1ce58ee |
completed | March 27, 2026, 7:07 p.m. |
| PD | Predicate disambiguation | batch_69c6d09bb4f881909bf20c188cb3e8e1 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:18 p.m.