Triple
T6231012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlin ABC |
E139351
|
entity |
| Predicate | fareScope |
P51453
|
FINISHED |
| Object | integrated tariff for multiple transport operators |
—
|
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 tariff for multiple transport operators | Statement: [Berlin ABC, fareScope, integrated tariff for multiple transport operators]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fareScope Context triple: [Berlin ABC, fareScope, integrated tariff for multiple transport operators]
-
A.
fareIntegrationScope
chosen
Indicates the extent to which fares are coordinated or unified across different transportation services or systems.
-
B.
fare
Indicates the price or cost required for a person or thing to be transported by a particular mode of travel or service.
-
C.
fareIntegration
Indicates that multiple transportation services or modes share a coordinated fare system, allowing passengers to use a single payment or ticket across them.
-
D.
fareModel
Indicates a pricing relationship where a specific fare structure, rule set, or calculation method is applied to determine the cost of a trip or service.
-
E.
fareAppliesTo
Indicates that a specific fare is applicable to a particular trip, service, passenger category, or travel condition.
- 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_69c008afd3148190b71e9eaa60420dd1 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062ec5be4819084d6df2e8dd2a542 |
completed | March 22, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69c05601de6481909d0880048fd7b49a |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:22 p.m.