Triple
T8901970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ORCA |
E211950
|
entity |
| Predicate | supportsFareCategory |
P8859
|
FINISHED |
| Object | adult 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: adult fares | Statement: [ORCA, supportsFareCategory, adult fares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsFareCategory Context triple: [ORCA, supportsFareCategory, adult fares]
-
A.
hasFareZoneFeature
Indicates that an entity is associated with a specific fare zone or fare-related area designation.
-
B.
hasFareZoneSystem
Indicates that an entity uses or is associated with a particular fare zone system for determining travel costs or ticketing.
-
C.
supportsRiderCategory
Indicates that one entity is capable of accommodating, enabling, or being compatible with a specified rider category.
-
D.
farePolicySupport
Indicates that there is a policy in place governing fares (such as prices, discounts, or rules) that is recognized, enabled, or supported in the given context.
-
E.
fareTypes
chosen
Indicates the categories or kinds of fares (e.g., ticket or pricing options) that apply to a given travel or service offering.
- 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_69ca83918d3081909b326fa3750cb8c8 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc642a104081908df2d64e8f9ad0c8 |
completed | April 1, 2026, 12:17 a.m. |
| PD | Predicate disambiguation | batch_69cc5c2bfb38819083d5eb1af8ccf4d6 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:55 p.m.