Triple
T36855845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Verkehrsverbund Rhein-Sieg |
E910791
|
entity |
| Predicate | hasTicketBrand |
P136845
|
FINISHED |
| Object | VRS ticket |
—
|
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: VRS ticket | Statement: [Verkehrsverbund Rhein-Sieg, hasTicketBrand, VRS ticket]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTicketBrand Context triple: [Verkehrsverbund Rhein-Sieg, hasTicketBrand, VRS ticket]
-
A.
hasTicket
Indicates that an entity possesses or holds a ticket, typically granting access, entry, or a right to a service or event.
-
B.
ticketingBrandAccepted
chosen
Indicates that a particular ticketing brand is recognized and accepted for use in a given context or system.
-
C.
hasEventBrand
Indicates that an event is associated with or organized under a particular brand.
-
D.
hasTicketMedia
Indicates that an entity possesses or is associated with a particular form or medium of a ticket (e.g., paper, digital, mobile).
-
E.
hasTicketIntegration
Indicates that there is an established connection enabling ticket-related data or actions to be shared or synchronized between systems or components.
- 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_69f76e8033d48190a59274f86f13be48 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fe38be079c8190a240191ac0e73e3a |
completed | May 8, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69fe350344508190930de2218156ca02 |
completed | May 8, 2026, 7:09 p.m. |
Created at: May 3, 2026, 4:13 p.m.