Triple
T902297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delhi Metro |
E19472
|
entity |
| Predicate | ticketingTechnology |
P3383
|
FINISHED |
| Object | automatic fare collection system |
—
|
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: automatic fare collection system | Statement: [Delhi Metro, ticketingTechnology, automatic fare collection system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ticketingTechnology Context triple: [Delhi Metro, ticketingTechnology, automatic fare collection system]
-
A.
hasTicketing
chosen
Indicates that an entity provides or is associated with a system or mechanism for issuing, managing, or selling tickets.
-
B.
ticketingCompatibleWith
Indicates that two systems, services, or components can interoperate or be used together within the same ticketing or reservation workflow without conflict.
-
C.
ticketedAttraction
Indicates that access to the attraction requires a purchased ticket or paid admission.
-
D.
sellsTicketsUnder
Indicates that one entity sells tickets at a price lower than or under the pricing of another entity.
-
E.
hasTicketRequirement
Indicates that an entity is subject to a specific ticket or admission requirement in order for access, participation, or use to be allowed.
- 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_69a4939e889c8190ac148b3ac1a7f90b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad56f4c08190a7a5091ff0eb3209 |
completed | March 1, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69a4aa98caec8190bbcc38320090f058 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.