Triple
T930092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | InterCity |
E20070
|
entity |
| Predicate | notableOperator |
P179
|
FINISHED |
| Object | Deutsche Bahn |
E22662
|
NE 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: Deutsche Bahn | Statement: [InterCity, notableOperator, Deutsche Bahn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Deutsche Bahn Context triple: [InterCity, notableOperator, Deutsche Bahn]
-
A.
Deutsche Bahn
chosen
Deutsche Bahn is Germany's state-owned national railway company and one of the largest rail and logistics operators in Europe.
-
B.
ProRail
ProRail is the Dutch government-owned company responsible for managing and maintaining the national railway infrastructure in the Netherlands.
-
C.
Nederlandse Spoorwegen
Nederlandse Spoorwegen is the principal Dutch railway company responsible for most passenger train services across the Netherlands.
-
D.
Swiss Federal Railways
Swiss Federal Railways is Switzerland’s national railway company, responsible for operating the majority of the country’s passenger and freight rail services and managing much of its rail infrastructure.
-
E.
Berliner Verkehrsbetriebe
Berliner Verkehrsbetriebe is Berlin’s main public transport company, operating the city’s extensive network of U-Bahn trains, trams, and buses.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a493af3dc48190adb7263e6e445ea1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b349b3d0819090c58b4fb60c6a1b |
completed | March 1, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7ee1108188190a26c73864c697061 |
completed | March 4, 2026, 8:32 a.m. |
Created at: March 1, 2026, 7:40 p.m.