Triple
T7430940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramanandi Sampradaya |
E171485
|
entity |
| Predicate | hasAsceticType |
P76365
|
FINISHED |
| Object | bairagis |
—
|
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: bairagis | Statement: [Ramanandi Sampradaya, hasAsceticType, bairagis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAsceticType Context triple: [Ramanandi Sampradaya, hasAsceticType, bairagis]
-
A.
hasBodhisattva
Indicates that one entity includes, is associated with, or is characterized by the presence or guidance of a bodhisattva.
-
B.
hasMonasticName
Indicates that an entity possesses a specific name adopted or assigned within a monastic or religious order.
-
C.
hasDeityAspect
Indicates that one entity embodies, represents, or functions as a specific divine aspect or manifestation of another deity.
-
D.
hasHolinessType
Indicates a relationship where an entity is assigned or associated with a specific type or category of holiness.
-
E.
asceticPracticeDuration
Indicates the length of time that an ascetic practice is or was undertaken.
- F. None of above. chosen
Provenance (4 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_69c68a63491881909281f73d4d5643bf |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f32324c481908c9ba594e8456728 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f038582c8190bac77c9b5a34b862 |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f0be2b1c8190bea06100a7caef2b |
completed | March 27, 2026, 9:03 p.m. |
Created at: March 27, 2026, 3:12 p.m.