Triple
T3381649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nord-Süd-Bahn |
E71198
|
entity |
| Predicate | hasRouteRole |
P36629
|
FINISHED |
| Object | major north–south axis in Berlin U-Bahn network |
—
|
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 north–south axis in Berlin U-Bahn network | Statement: [Nord-Süd-Bahn, hasRouteRole, major north–south axis in Berlin U-Bahn network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRouteRole Context triple: [Nord-Süd-Bahn, hasRouteRole, major north–south axis in Berlin U-Bahn network]
-
A.
hasRoute
Indicates that there exists a path or connection enabling travel or communication from one entity to another.
-
B.
hasRole
Indicates that an entity occupies, performs, or is assigned a specific role or function in relation to another entity or context.
-
C.
hasRouteType
Indicates that there is a specific kind or category of route associated with an entity (e.g., road, rail, bus line).
-
D.
hasRouteFeature
Indicates that a route possesses or is associated with a specific characteristic, attribute, or feature.
-
E.
routeRole
chosen
Indicates the specific functional role or purpose that an entity has within a particular route or path.
- 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_69ad85a8fd9c819095ecedf838d2bf1b |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb5e9af608190bfb228ef99a87bb7 |
completed | March 8, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69ada434bae48190a77ea37f9274ad8f |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:14 p.m.