Triple
T25424916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Miles points |
E637093
|
entity |
| Predicate | rewardTypeFor |
P146363
|
FINISHED |
| Object | Eastern Miles members |
—
|
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: Eastern Miles members | Statement: [Eastern Miles points, rewardTypeFor, Eastern Miles members]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rewardTypeFor Context triple: [Eastern Miles points, rewardTypeFor, Eastern Miles members]
-
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.
rewardScope
chosen
Indicates the extent, range, or conditions under which a reward applies within a given context or system.
-
E.
rewardModel
Indicates a relationship where one entity serves as a model or framework for assigning rewards or evaluating outcomes for another entity or 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_69e75db58a1c8190891b9ff7c2f8414e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f6bf25c881909f049d5393927bfb |
completed | May 2, 2026, 1:06 p.m. |
| PD | Predicate disambiguation | batch_69f45d0dbc8c8190beecce679fce90a4 |
completed | May 1, 2026, 7:58 a.m. |
Created at: April 21, 2026, 1:57 p.m.