Triple
T14882680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hindu varna system |
E350037
|
entity |
| Predicate | hasIdealPrinciple |
P17030
|
FINISHED |
| Object | division according to qualities and duties |
—
|
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: division according to qualities and duties | Statement: [Hindu varna system, hasIdealPrinciple, division according to qualities and duties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIdealPrinciple Context triple: [Hindu varna system, hasIdealPrinciple, division according to qualities and duties]
-
A.
hasIdeal
Indicates that an entity holds or is associated with a guiding principle, standard, or value it considers perfect or most desirable.
-
B.
hasEthicalIdeal
Indicates that an entity upholds or is guided by a particular ethical standard, principle, or ideal.
-
C.
coreIdeal
chosen
Indicates that something is a fundamental, central principle or value that defines or strongly guides another entity.
-
D.
implementsPrinciple
Indicates that an entity applies, follows, or puts into practice a specified principle in its design, behavior, or operation.
-
E.
hasIdealization
Indicates that one entity is a simplified, abstracted, or ideal form or model of another entity, capturing its essential features while omitting complexities.
- 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_69d822ee4f408190b6ac3b2fa434f0df |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5e7c0e48190af2d68a71130585c |
completed | April 15, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69de8c1a2bcc81908f914e2e2ced65eb |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:56 a.m.