Triple
T32265741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chase Sapphire Preferred Card |
E824277
|
entity |
| Predicate | bonusCategory |
P173899
|
FINISHED |
| Object | travel |
—
|
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: travel | Statement: [Chase Sapphire Preferred Card, bonusCategory, travel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bonusCategory Context triple: [Chase Sapphire Preferred Card, bonusCategory, travel]
-
A.
rewardBrand
Indicates that one entity grants or associates a reward with a particular brand.
-
B.
supportsBonus
Indicates that one entity provides or enables an additional benefit, reward, or bonus for another entity.
-
C.
badgeCategory
Indicates the classification or type group to which a particular badge belongs.
-
D.
awardCurrency
Indicates that one entity grants or gives a specified amount of currency to another entity.
-
E.
awardEffect
Indicates that one entity confers or grants a benefit, recognition, or reward that has a particular impact or consequence on 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_69f3490e73588190915f282edd105772 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bc7f0ef081909966c28aafcb9bc3 |
completed | May 3, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69f6b632cf788190a3d0c08cd026b84b |
completed | May 3, 2026, 2:42 a.m. |
| PDg | Predicate description generation | batch_69f6b960ca4081909a77690c2b122f5e |
completed | May 3, 2026, 2:56 a.m. |
Created at: May 1, 2026, 12:42 a.m.