Triple
T17721647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adult Opal card |
E442350
|
entity |
| Predicate | fareProductType |
P128722
|
FINISHED |
| Object | distance-based fares |
—
|
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: distance-based fares | Statement: [Adult Opal card, fareProductType, distance-based fares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fareProductType Context triple: [Adult Opal card, fareProductType, distance-based fares]
-
A.
fareProduct
Indicates a relationship where a specific fare or price offering is associated with a particular product or service option.
-
B.
fareType
Indicates the category or class of fare (such as standard, discounted, or promotional) that applies to a given trip, ticket, or pricing instance.
-
C.
fareTypes
Indicates the categories or kinds of fares (e.g., ticket or pricing options) that apply to a given travel or service offering.
-
D.
fareModel
Indicates a pricing relationship where a specific fare structure, rule set, or calculation method is applied to determine the cost of a trip or service.
-
E.
fareAppliesTo
Indicates that a specific fare is applicable to a particular trip, service, passenger category, or travel condition.
- 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47486438c8190abe27eb4eb2c6fdf |
completed | April 19, 2026, 6:21 a.m. |
| PD | Predicate disambiguation | batch_69e3cde601d4819097903f471f1fe99a |
completed | April 18, 2026, 6:31 p.m. |
| PDg | Predicate description generation | batch_69e3d018227c8190b6624a2199e765e8 |
completed | April 18, 2026, 6:40 p.m. |
Created at: April 10, 2026, 10:07 a.m.