Triple
T14381037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siemens EuroSprinter |
E356600
|
entity |
| Predicate | operator |
P179
|
FINISHED |
| Object | ÖBB |
E112020
|
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: ÖBB | Statement: [Siemens EuroSprinter, operator, ÖBB]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ÖBB Context triple: [Siemens EuroSprinter, operator, ÖBB]
-
A.
ÖBB
chosen
ÖBB is Austria’s national railway company, operating most of the country’s passenger and freight train services across domestic and international routes.
-
B.
Deutsche Bahn
Deutsche Bahn is Germany's state-owned national railway company and one of the largest rail and logistics operators in Europe.
-
C.
Südostbahn
Südostbahn is a Swiss railway company that operates regional and suburban train services, including lines within the Zürich S-Bahn network.
-
D.
Slovenske železnice
Slovenske železnice is Slovenia’s national railway company, responsible for operating the country’s passenger and freight rail services and managing much of its rail infrastructure.
-
E.
Vienna Wiener Linien
Vienna Wiener Linien is the municipal public transport operator in Vienna, Austria, responsible for the city’s extensive tram, bus, and metro networks.
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de900bbfb08190a1e56f281a2374c0 |
completed | April 14, 2026, 7:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c590660819090652e75418f2747 |
completed | May 8, 2026, 2:37 a.m. |
Created at: April 10, 2026, 1:16 a.m.