Triple
T14057009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DOT (Din Offentlige Transport) |
E338244
|
entity |
| Predicate | ticketSystemType |
P112657
|
FINISHED |
| Object | integrated fare 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: integrated fare system | Statement: [DOT (Din Offentlige Transport), ticketSystemType, integrated fare system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ticketSystemType Context triple: [DOT (Din Offentlige Transport), ticketSystemType, integrated fare system]
-
A.
ticketSystem
Indicates a relationship where an entity is managed, tracked, or processed through a ticket-based system for handling requests, issues, or tasks.
-
B.
ticketModel
Indicates a relationship where an entity is associated with, or represented by, a specific ticket model or ticket-type specification.
-
C.
primaryTicketingSystem
Indicates that one ticketing system is designated as the main or default system used for handling tickets in a given context.
-
D.
issueType
Indicates the specific category or classification assigned to an issue within a tracking or management context.
-
E.
ticketTypeExample
Indicates that an entity serves as an example or illustrative instance of a particular ticket type.
- F. None of above. chosen
Provenance (4 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de3c8e6d008190af8892f34c5cefbd |
completed | April 14, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69de05adef888190b023ab42ef5076b6 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de2398856c81908bed6070e4ca6ab1 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:20 p.m.