Triple
T1959778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal Aérea |
E42354
|
entity |
| Predicate | ticketingMedium |
P29575
|
FINISHED |
| Object | Tarjeta de Movilidad Integrada |
—
|
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: Tarjeta de Movilidad Integrada | Statement: [Terminal Aérea, ticketingMedium, Tarjeta de Movilidad Integrada]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ticketingMedium Context triple: [Terminal Aérea, ticketingMedium, Tarjeta de Movilidad Integrada]
-
A.
ticketingCompatibleWith
Indicates that two systems, services, or components can interoperate or be used together within the same ticketing or reservation workflow without conflict.
-
B.
hasTicketing
Indicates that an entity provides or is associated with a system or mechanism for issuing, managing, or selling tickets.
-
C.
ticketDemand
Indicates that there is a level of desire or need among potential buyers for tickets to an event, service, or offering.
-
D.
ticket
chosen
Indicates that an entity serves as or is associated with a ticket, typically representing authorization, access, or a record for an event, service, or transaction.
-
E.
ticketedAttraction
Indicates that access to the attraction requires a purchased ticket or paid admission.
- 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_69a8870eea088190a38781990812a9bc |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb68a8e608190bc37a85913b3cd44 |
completed | March 7, 2026, 5:24 a.m. |
| PD | Predicate disambiguation | batch_69abaff5dbd48190a9d36ca60de151db |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.