Triple
T2280446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barcelona Metro |
E51267
|
entity |
| Predicate | ticketingZoneSystem |
P3383
|
FINISHED |
| Object | ATM fare zones |
—
|
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: ATM fare zones | Statement: [Barcelona Metro, ticketingZoneSystem, ATM fare zones]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ticketingZoneSystem Context triple: [Barcelona Metro, ticketingZoneSystem, ATM fare zones]
-
A.
ticketingZoneType
Indicates the type or category of ticketing zone that applies within a given area or context.
-
B.
hasTicketing
chosen
Indicates that an entity provides or is associated with a system or mechanism for issuing, managing, or selling tickets.
-
C.
ticketingCompatibleWith
Indicates that two systems, services, or components can interoperate or be used together within the same ticketing or reservation workflow without conflict.
-
D.
hasFareZone
Indicates that an entity is located within or associated with a specific fare zone used for pricing or ticketing.
-
E.
seatNotationSystem
Indicates the system or convention used to label, number, or otherwise denote seats within a venue or vehicle.
- 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_69a88b08e4308190bdac9aebcca1c91a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc21ac3d48190abef254e1c3f45e8 |
completed | March 7, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69abbdb9aa3c819088d0316c5269a1c2 |
completed | March 7, 2026, 5:55 a.m. |
Created at: March 4, 2026, 7:48 p.m.