Triple
T2586448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surah Nuh |
E58015
|
entity |
| Predicate | emphasizesAct |
P17414
|
FINISHED |
| Object | seeking forgiveness from Allah |
—
|
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: seeking forgiveness from Allah | Statement: [Surah Nuh, emphasizesAct, seeking forgiveness from Allah]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emphasizesAct Context triple: [Surah Nuh, emphasizesAct, seeking forgiveness from Allah]
-
A.
hasEmphasis
chosen
Indicates that one element is given special stress, importance, or prominence relative to others.
-
B.
positionEmphasized
Indicates that a particular position, stance, or role is given special prominence or stress relative to others.
-
C.
strategyEmphasis
Indicates an entity’s primary focus or priority within a broader strategy or plan.
-
D.
mottoEmphasizes
Indicates that a motto highlights, stresses, or gives special importance to a particular idea, value, or theme.
-
E.
closingEmphasis
Indicates that one entity concludes or reinforces another entity’s point, action, or message with particular stress or importance.
- 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_69ab4ac019c8819094add11c46706e32 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd3f6f6ac8190abff7b8b6ff3c023 |
completed | March 7, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69abd0d19308819089ee942513d567a4 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:49 p.m.