Triple
T29210827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inbam |
E740540
|
entity |
| Predicate | moralAim |
P168650
|
FINISHED |
| Object | to regulate and refine human love |
—
|
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: to regulate and refine human love | Statement: [Inbam, moralAim, to regulate and refine human love]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moralAim Context triple: [Inbam, moralAim, to regulate and refine human love]
-
A.
moralCriterion
Indicates that something is being evaluated or classified according to a standard of moral judgment or ethical rightness.
-
B.
moralRealization
Indicates the recognition or coming to understand a moral truth, principle, or ethical implication about a situation or action.
-
C.
moralAttitude
Indicates a subject’s evaluative stance or judgment about the moral rightness or wrongness of another entity, action, or situation.
-
D.
moralConcept
Indicates that one entity represents or embodies a moral or ethical concept in relation to another.
-
E.
moralTrajectory
Indicates the direction and pattern of change in an entity’s moral behavior or ethical stance over time.
- 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_69f07cba2f808190a2746477d4e8345b |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f67595fa7c8190b6e9f7a8c700dd97 |
completed | May 2, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69f673c4abec8190bc2379e66f4af0a9 |
completed | May 2, 2026, 9:59 p.m. |
| PDg | Predicate description generation | batch_69f674df80b08190adb7f7531083bbb1 |
completed | May 2, 2026, 10:04 p.m. |
Created at: April 28, 2026, 12:11 p.m.