Triple
T26747505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EVE |
E674439
|
entity |
| Predicate | usedInPassengerTicketing |
P38658
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [EVE, usedInPassengerTicketing, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInPassengerTicketing Context triple: [EVE, usedInPassengerTicketing, true]
-
A.
usedInRailwayTickets
Indicates that something is employed or applied in the context of railway tickets, such as their creation, validation, or usage.
-
B.
usedInE-tickets
chosen
Indicates that something (such as a method, technology, or feature) is employed or applied within the context of electronic tickets (e-tickets).
-
C.
usedForPassengerInformation
Indicates that something serves the purpose of providing information to passengers.
-
D.
usedForTicketType
Indicates that something is utilized or applicable for a specific type or category of ticket.
-
E.
usedBetweenStations
Indicates that something (such as a service, route, or resource) is utilized in the context of travel or operation between two stations.
- 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_69eecda63a3881908095c47900692e65 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f6db1f3ec48190a82e7d893d3c76ba |
completed | May 3, 2026, 5:20 a.m. |
| PD | Predicate disambiguation | batch_69f6d82adfa481908a5e196d2e18c73f |
completed | May 3, 2026, 5:07 a.m. |
Created at: April 27, 2026, 3:52 a.m.