Triple
T38661112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upatiṣya |
E940333
|
entity |
| Predicate | isExemplarOf |
P135707
|
FINISHED |
| Object | ideal disciple |
—
|
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: ideal disciple | Statement: [Upatiṣya, isExemplarOf, ideal disciple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isExemplarOf Context triple: [Upatiṣya, isExemplarOf, ideal disciple]
-
A.
isCanonicalExampleOf
chosen
Indicates that something serves as a standard or typical instance that exemplifies a concept, category, or pattern.
-
B.
isClassicalExampleOf
Indicates that something serves as a standard or widely recognized instance illustrating the defining features of a particular concept, category, or phenomenon.
-
C.
isRepresentiveOf
Indicates that one entity serves as an official agent, spokesperson, or proxy acting on behalf of another entity.
-
D.
isModelOf
Indicates that one entity serves as a representation or abstraction that captures the structure or behavior of another entity.
-
E.
isDemoOf
Indicates that one entity serves as a demonstration, example, or illustrative instance of another entity.
- 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_69f76edfde348190bf6529d9f49ecd62 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:33 p.m.