Triple
T10576511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | pramāṇa theory |
E249623
|
entity |
| Predicate | variesBySchool |
P94716
|
FINISHED |
| Object | number of accepted pramāṇas |
—
|
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: number of accepted pramāṇas | Statement: [pramāṇa theory, variesBySchool, number of accepted pramāṇas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: variesBySchool Context triple: [pramāṇa theory, variesBySchool, number of accepted pramāṇas]
-
A.
publicSchool
Indicates that an educational institution is operated and funded by a government or public authority rather than by private entities.
-
B.
awaySchool
Indicates that an entity is located away from or not present at their usual school.
-
C.
partnerSchool
Indicates a formal collaborative relationship between two educational institutions, typically involving shared programs, resources, or exchange activities.
-
D.
schoolRoll
Indicates the official list or record of students enrolled in a particular school or class.
-
E.
hasAlternativeSchool
Indicates that an entity is associated with another school option that can serve as a substitute or backup to the primary school.
- 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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5275628988190bd00dd3f8d7c3937 |
completed | April 7, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69d51901ff6c819095e7b528170a69dc |
completed | April 7, 2026, 2:47 p.m. |
| PDg | Predicate description generation | batch_69d5270eca0481908573b698390c5b08 |
completed | April 7, 2026, 3:47 p.m. |
Created at: April 6, 2026, 12:38 p.m.