Triple
T2586450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surah Nuh |
E58015
|
entity |
| Predicate | mentionsReward |
P36807
|
FINISHED |
| Object | worldly blessings for repentance |
—
|
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: worldly blessings for repentance | Statement: [Surah Nuh, mentionsReward, worldly blessings for repentance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mentionsReward Context triple: [Surah Nuh, mentionsReward, worldly blessings for repentance]
-
A.
rewardUse
Indicates that one entity grants or provides a reward in response to the use or utilization of another entity.
-
B.
grantedAsRewardFor
Indicates that something is given to an entity specifically as a reward for a particular action, achievement, or service.
-
C.
rewardFulfilledFor
Indicates that a previously promised or expected reward has been delivered or satisfied for a particular entity.
-
D.
describesReward
chosen
Indicates that one entity provides an explanation or specification of the reward associated with another entity or action.
-
E.
rewardSignal
Indicates that one entity provides a signal representing feedback or incentive (such as a reward or penalty) to guide another entity’s behavior or learning process.
- 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.