Triple
T15238341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Petronas Mesra |
E364187
|
entity |
| Predicate | loyaltyBenefit |
P57184
|
FINISHED |
| Object | earn points on fuel |
—
|
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: earn points on fuel | Statement: [Petronas Mesra, loyaltyBenefit, earn points on fuel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loyaltyBenefit Context triple: [Petronas Mesra, loyaltyBenefit, earn points on fuel]
-
A.
loyaltyIncentive
chosen
Indicates a relationship where benefits or rewards are provided to encourage or recognize continued commitment or repeat engagement.
-
B.
loyaltySymbolizedBy
Indicates that an instance of loyalty is represented or expressed by a particular symbol or emblem.
-
C.
loyaltyIntegration
Indicates the degree to which a loyalty or rewards program is connected, synchronized, or functionally embedded with another system, platform, or service.
-
D.
loyaltyDimension
Indicates the degree or aspect of loyalty characterizing the relationship between entities.
-
E.
loyaltyMechanism
Indicates a mechanism or process through which loyalty is established, maintained, or reinforced between entities.
- 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_69d85a0dde7481908fc64d1e82d5d20d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007da7e988190925a9b67b8070bc7 |
completed | April 15, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69deca899d5c8190be4a7c71e1683c69 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:12 a.m.