Triple
T2229829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asia Miles |
E48737
|
entity |
| Predicate | loyaltyCurrencyCanBeEarnedFrom |
P35525
|
FINISHED |
| Object | credit card spend |
—
|
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: credit card spend | Statement: [Asia Miles, loyaltyCurrencyCanBeEarnedFrom, credit card spend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: loyaltyCurrencyCanBeEarnedFrom Context triple: [Asia Miles, loyaltyCurrencyCanBeEarnedFrom, credit card spend]
-
A.
loyaltyProgramEarnings
Indicates the amount or details of rewards or benefits a participant accrues within a loyalty or rewards program.
-
B.
loyaltyProgramType
Indicates the specific category or kind of loyalty program associated with an entity (such as points-based, tiered, or subscription-based).
-
C.
earnsRewardsCurrency
chosen
Indicates that an entity receives or accumulates a specified rewards currency as a result of some action, status, or relationship.
-
D.
supportsLoyaltyCards
Indicates that an entity provides functionality to accept, manage, or work with loyalty cards for rewards or benefits.
-
E.
loyaltyProgramTierOf
Indicates the specific loyalty or rewards program tier that an entity (such as a customer or account) belongs to.
- 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_69a88aa51b388190949868ec9766e587 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc069e0ac8190bcda8cba9f5c7a5d |
completed | March 7, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69abbdadbb0c8190b3a1ede31b8acbfa |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.