Triple
T33601225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BART distance-based fare system |
E860724
|
entity |
| Predicate | offersDiscountTo |
P9238
|
FINISHED |
| Object | youth riders |
—
|
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: youth riders | Statement: [BART distance-based fare system, offersDiscountTo, youth riders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersDiscountTo Context triple: [BART distance-based fare system, offersDiscountTo, youth riders]
-
A.
offersDiscountsOn
chosen
Indicates that one entity provides price reductions or special discount deals specifically applied to another entity or its associated items or services.
-
B.
supportsDiscounts
Indicates that an entity provides or is compatible with special price reductions or promotional discounts.
-
C.
offersPass
Indicates that one entity provides or makes available a pass (such as a ticket, permit, or access credential) to another entity.
-
D.
offersIncentive
Indicates that one entity provides a reward, benefit, or motivation to another entity to encourage a specific action or behavior.
-
E.
offersProgram
Indicates that an entity provides or makes available a specific program (such as a course, curriculum, or initiative).
- 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_69f3497f35908190a2e9bbb9b96c7a3f |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fdb04ed81c8190b8feea90c1c785a6 |
completed | May 8, 2026, 9:43 a.m. |
| PD | Predicate disambiguation | batch_69fda9d6c5148190a63205b6d9b0a1b4 |
completed | May 8, 2026, 9:16 a.m. |
Created at: May 1, 2026, 1:41 a.m.