Triple
T25205461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bavarian Railway Museum |
E631238
|
entity |
| Predicate | locatedInBuildingOrStructure |
P166606
|
FINISHED |
| Object | former Nördlingen locomotive depot |
—
|
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: former Nördlingen locomotive depot | Statement: [Bavarian Railway Museum, locatedInBuildingOrStructure, former Nördlingen locomotive depot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInBuildingOrStructure Context triple: [Bavarian Railway Museum, locatedInBuildingOrStructure, former Nördlingen locomotive depot]
-
A.
locatedOnBuilding
Indicates that one entity is physically situated on the exterior or rooftop surface of a building.
-
B.
locatedInBuildingUsedAs
Indicates that something is located inside a building that is being used for a specified purpose or function.
-
C.
locatedInBuildingWithFeature
Indicates that something is located in a building that possesses a specified feature or characteristic.
-
D.
isLocatedInBuilding
chosen
Indicates that one entity is physically situated within or inside the structure of a particular building.
-
E.
occursInBuilding
Indicates that an event or activity takes place within a specific building.
- 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_69e75a8b86c4819089eda22c843b739f |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 21, 2026, 12:52 p.m.