Triple
T27835772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | エポスカード |
E703221
|
entity |
| Predicate | ポイント利用方法 |
P107989
|
FINISHED |
| Object | 商品券やギフト券と交換できる |
—
|
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: 商品券やギフト券と交換できる | Statement: [エポスカード, ポイント利用方法, 商品券やギフト券と交換できる]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ポイント利用方法 Context triple: [エポスカード, ポイント利用方法, 商品券やギフト券と交換できる]
-
A.
creditsUse
Indicates that one entity uses or relies on credits (such as credit units, credit lines, or credit-based resources) provided or available to it.
-
B.
usesPointsSystem
Indicates that an entity operates or functions based on a structured points-based system for evaluation, rewards, or progression.
-
C.
loyaltyCurrencyUse
chosen
Indicates the use or redemption of loyalty program currency (such as points or miles) in a transaction or activity.
-
D.
rewardUse
Indicates that one entity grants or provides a reward in response to the use or utilization of another entity.
-
E.
usesPromotion
Indicates that an entity applies or takes advantage of a specific promotion, discount, or special offer.
- 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_69ef840b94b08190950a4f77296938b2 |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f63b317e048190963989b732b25b91 |
completed | May 2, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69f6370ea79c81909b761821ee0fa698 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 5:59 p.m.