Triple
T11904348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stuttgart Stadtbahn |
E283234
|
entity |
| Predicate | hasDepot |
P2413
|
FINISHED |
| Object | Betriebshof Möhringen |
E364072
|
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: Betriebshof Möhringen | Statement: [Stuttgart Stadtbahn, hasDepot, Betriebshof Möhringen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Betriebshof Möhringen Context triple: [Stuttgart Stadtbahn, hasDepot, Betriebshof Möhringen]
-
A.
Scheibenhof
Scheibenhof is a locality or district that forms part of the city of Krems an der Donau in Lower Austria.
-
B.
Möhringen
chosen
Möhringen is a district of Stuttgart in the German state of Baden-Württemberg, known as a residential area that also hosts U.S. military facilities.
-
C.
Hartmannshof
Hartmannshof is a locality in Bavaria, Germany, that functions as an outer terminus on the Nuremberg S-Bahn commuter rail network.
-
D.
Ronsdorf
Ronsdorf is a district of the German city of Wuppertal in North Rhine-Westphalia, historically known as an independent town in the Bergisches Land region.
-
E.
Oberkassel
Oberkassel is a riverside district of Düsseldorf in western Germany, known for its affluent residential areas and scenic location along the Rhine.
- 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_69d6ab2c07e88190ba13b0d21fd6cf33 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8e525460c81909d855048d9c799bf |
completed | April 10, 2026, 11:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f418487f448190b6e24fb2c0409e3f |
completed | May 1, 2026, 3:04 a.m. |
Created at: April 8, 2026, 9:44 p.m.