Triple
T6475162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berlin tram |
E146051
|
entity |
| Predicate | ridershipRole |
P6821
|
FINISHED |
| Object | major share of surface public transport in eastern Berlin |
—
|
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: major share of surface public transport in eastern Berlin | Statement: [Berlin tram, ridershipRole, major share of surface public transport in eastern Berlin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ridershipRole Context triple: [Berlin tram, ridershipRole, major share of surface public transport in eastern Berlin]
-
A.
ridershipLevel
Indicates the magnitude or intensity of usage by riders or passengers for a given service, route, or system.
-
B.
mobilityRole
Indicates the functional role or capacity an entity has in enabling, supporting, or performing movement or transportation.
-
C.
transportationRole
chosen
Indicates a role or function that an entity has specifically in the context of providing, operating, or supporting transportation.
-
D.
notableRiderType
Indicates that an entity is notably associated with a particular type or category of rider (e.g., cyclist, jockey, driver).
-
E.
primaryRiders
Indicates that the referenced entities are the main or principal riders associated with a particular vehicle, trip, or ride-related event.
- 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_69c008fec7408190af7b146dc63d9750 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a341360819082f2b5496a1a68b0 |
completed | March 22, 2026, 10:16 p.m. |
| PD | Predicate disambiguation | batch_69c0673f6d48819080e10c85155c7195 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:50 p.m.