Triple
T12762249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greyhound Canada |
E305022
|
entity |
| Predicate | offeredDiscount |
P9238
|
FINISHED |
| Object | student discounts |
—
|
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: student discounts | Statement: [Greyhound Canada, offeredDiscount, student discounts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offeredDiscount Context triple: [Greyhound Canada, offeredDiscount, student discounts]
-
A.
discountRate
Indicates the percentage or amount by which a price, cost, or value is reduced relative to its original level.
-
B.
discountMechanism
Indicates a relationship where one entity defines the method, rule, or process by which a discount is calculated, applied, or granted to another entity.
-
C.
offersDiscountsOn
chosen
Indicates that one entity provides price reductions or special discount deals specifically applied to another entity or its associated items or services.
-
D.
fareDiscount
Indicates that a reduced price is applied to a standard fare for a product or service.
-
E.
offersIncentive
Indicates that one entity provides a reward, benefit, or motivation to another entity to encourage a specific action or behavior.
- 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_69d7bdf1fcd081909ffb0e0d6fa3a07d |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d8e44188190840cd23d380bf23d |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96409739881909174ba005a986cb5 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:28 p.m.