Triple
T38302419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erlangen public bus network |
E1032254
|
entity |
| Predicate | typicalTicketing |
P204586
|
FINISHED |
| Object | public transport 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: public transport tickets | Statement: [Erlangen public bus network, typicalTicketing, public transport tickets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTicketing Context triple: [Erlangen public bus network, typicalTicketing, public transport tickets]
-
A.
ticketingContext
Indicates the situational or operational context in which a ticket (such as a support, event, or issue ticket) is created, managed, or applied.
-
B.
typicalTicketText
Indicates that the associated text represents the standard or commonly used wording for a ticket.
-
C.
ticketingFor
Indicates that one entity is responsible for issuing, managing, or providing tickets for another entity, such as an event, service, or venue.
-
D.
ticketTypeCommon
Indicates that two or more tickets share the same general type or classification.
-
E.
ticketingTreatment
Indicates how an entity is handled or processed within a ticketing or issue-tracking workflow.
- 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_69f76e0f2084819091299d021625c3fe |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:30 p.m.