Triple
T4428792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nuremberg public transport network |
E95272
|
entity |
| Predicate | supportsTicketType |
P24486
|
FINISHED |
| Object | single tickets |
—
|
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: single tickets | Statement: [Nuremberg public transport network, supportsTicketType, single tickets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsTicketType Context triple: [Nuremberg public transport network, supportsTicketType, single tickets]
-
A.
supportsType
chosen
Indicates that one entity is capable of handling, accepting, or being compatible with a specified type.
-
B.
supportsParticipantType
Indicates that an entity is compatible with, or designed to work with, a specified type or category of participant.
-
C.
supportsProgramType
Indicates that one entity is capable of handling, offering, or being compatible with a specified type of program.
-
D.
ticketingCompatibleWith
Indicates that two systems, services, or components can interoperate or be used together within the same ticketing or reservation workflow without conflict.
-
E.
supportsMissionType
Indicates that one entity is capable of handling, enabling, or being compatible with a specified type of mission.
- 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_69b3453c2a0c8190926b574c90766db9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35568767c819084d5e18b56a4745e |
completed | March 13, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69b34f5eabe88190a12b244ea71e46d6 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:30 p.m.