Triple
T15849304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | story of Baucis and Philemon |
E384293
|
entity |
| Predicate | rewardForCharacters |
P120108
|
FINISHED |
| Object | priesthood of the temple |
—
|
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: priesthood of the temple | Statement: [story of Baucis and Philemon, rewardForCharacters, priesthood of the temple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rewardForCharacters Context triple: [story of Baucis and Philemon, rewardForCharacters, priesthood of the temple]
-
A.
rewardForCompletion
Indicates that something is given as a benefit or compensation in return for successfully completing a task, activity, or objective.
-
B.
monetaryReward
Indicates that one entity provides or promises a payment of money to another as compensation, incentive, or prize.
-
C.
awardCurrency
Indicates that one entity grants or gives a specified amount of currency to another entity.
-
D.
rewardInHereafter
Indicates that an action or state results in a positive recompense or benefit granted in the afterlife.
-
E.
rewardUse
Indicates that one entity grants or provides a reward in response to the use or utilization of another entity.
- 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_69d86da422088190aac39e32e6c68429 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e14caa3fa481909bd01f3b901d7716 |
completed | April 16, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69e005434ed88190baf11c169da3cf29 |
completed | April 15, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69e007869ae481909473ee220a7ccdb5 |
completed | April 15, 2026, 9:47 p.m. |
Created at: April 10, 2026, 4:50 a.m.