Triple
T3824954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Verkehrsverbund Großraum Nürnberg |
E88663
|
entity |
| Predicate | typeOfFareSystem |
P395
|
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: [Verkehrsverbund Großraum Nürnberg, typeOfFareSystem, integrated fare system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfFareSystem Context triple: [Verkehrsverbund Großraum Nürnberg, typeOfFareSystem, integrated fare system]
-
A.
fareSystem
chosen
Indicates a relationship where a system is used to determine, collect, or manage fares or payments for transportation or similar services.
-
B.
fareTypes
Indicates the categories or kinds of fares (e.g., ticket or pricing options) that apply to a given travel or service offering.
-
C.
fareType
Indicates the category or class of fare (such as standard, discounted, or promotional) that applies to a given trip, ticket, or pricing instance.
-
D.
appliesToTransitSystem
Indicates that something (such as a rule, policy, feature, or condition) is relevant or applicable to a particular transit or transportation system.
-
E.
partOfTransitSystem
Indicates that something is a component or segment within a larger transit or transportation system.
- 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_69aed9538cf881909d9ce8ca4ac7c18c |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef188b474819087680db42b04ecdd |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee74a2bc081909b237df8b1e27653 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:17 p.m.