Triple
T26725384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samavayanga |
E673821
|
entity |
| Predicate | doctrineAspect |
P17738
|
FINISHED |
| Object | ethical classifications |
—
|
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: ethical classifications | Statement: [Samavayanga, doctrineAspect, ethical classifications]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: doctrineAspect Context triple: [Samavayanga, doctrineAspect, ethical classifications]
-
A.
testsAspect
Indicates that one entity evaluates, examines, or assesses a particular aspect, feature, or dimension of another entity.
-
B.
onAspect
Indicates that one entity is positioned on a particular side, surface, or facet of another entity.
-
C.
doctrineFocus
chosen
Indicates that a doctrine, teaching, or belief is primarily concerned with, centered on, or directed toward a particular subject or theme.
-
D.
doctrineSupported
Indicates that one entity endorses, upholds, or provides backing for a particular doctrine or set of principles.
-
E.
appliedDoctrine
Indicates that a particular doctrine, principle, or rule has been put into practice or used in interpreting or deciding a specific case, situation, or context.
- 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_69eecda481d08190aea69f2f7c745f56 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f6352fdb788190b9bad30243690743 |
completed | May 2, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69f631850ae08190a0ba51e4f1e4ccb3 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 3:42 a.m.