Triple
T17970538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rewards4All |
E449326
|
entity |
| Predicate | rewardMedium |
P91380
|
FINISHED |
| Object | points |
—
|
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: points | Statement: [Rewards4All, rewardMedium, points]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rewardMedium Context triple: [Rewards4All, rewardMedium, points]
-
A.
awardMedium
Indicates the medium or format through which an award is given, presented, or communicated.
-
B.
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.
-
C.
rewardUse
Indicates that one entity grants or provides a reward in response to the use or utilization of another entity.
-
D.
gainMediumState
Indicates that an entity transitions into or acquires a medium-level state or condition within a defined scale or process.
-
E.
rewardUnit
chosen
Indicates that one entity serves as the unit or measure in which a reward is quantified or granted to another entity.
- 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_69d8b9f9927c8190a006110c8b996e61 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b1fa67c48190936f20cea45e4599 |
completed | April 19, 2026, 10:44 a.m. |
| PD | Predicate disambiguation | batch_69e3f8fa62688190a5d5c361ab896256 |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:22 a.m.