Triple
T36178507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U-Bahn |
E1046642
|
entity |
| Predicate | typicalTicketSystem |
P204778
|
FINISHED |
| Object | integrated public transport fares |
—
|
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 public transport fares | Statement: [U-Bahn, typicalTicketSystem, integrated public transport fares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTicketSystem Context triple: [U-Bahn, typicalTicketSystem, integrated public transport fares]
-
A.
ticketSystemType
Indicates the type or category of ticketing system associated with an entity or interaction.
-
B.
ticketSystem
Indicates a relationship where an entity is managed, tracked, or processed through a ticket-based system for handling requests, issues, or tasks.
-
C.
primaryTicketingSystem
Indicates that one ticketing system is designated as the main or default system used for handling tickets in a given context.
-
D.
typicalTicketText
Indicates that the associated text represents the standard or commonly used wording for a ticket.
-
E.
resultingTicket
Indicates that one entity is the ticket that is produced or generated as the outcome of another entity or process.
- 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_69f76e3c1b10819081fc7a807a71cf84 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0a54cc8190868c1bfa1590d1a6 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82f8c88190bd77a086023ac0e1 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:08 p.m.