Triple
T2781239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Historisches Museum Frankfurt |
E61698
|
entity |
| Predicate | usesBuilding |
P1267
|
FINISHED |
| Object | Saalhof |
E301852
|
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: Saalhof | Statement: [Historisches Museum Frankfurt, usesBuilding, Saalhof]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saalhof Context triple: [Historisches Museum Frankfurt, usesBuilding, Saalhof]
-
A.
Saalhof
chosen
Saalhof is a historic medieval building complex in Frankfurt am Main that forms part of the city’s museum landscape and reflects its architectural and urban history.
-
B.
Selhof
Selhof is a district of the German town of Bad Honnef in the state of North Rhine-Westphalia.
-
C.
Schöngarth
Schöngarth is a German surname most notably associated with Eberhard Schöngarth, a high-ranking Nazi SS officer and war criminal during World War II.
-
D.
Reundorf
Reundorf is a village-level subdivision of the town of Lichtenfels in the Upper Franconia region of Bavaria, Germany.
-
E.
Schaafheim
Schaafheim is a municipality in the state of Hesse in central Germany.
- 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_69ab4b7e43c48190997b8fc8fb1663ab |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdd997ebc8190bff88fe549827615 |
completed | March 7, 2026, 8:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afe8a126f881909c378eca59b570a0 |
completed | March 10, 2026, 9:47 a.m. |
Created at: March 6, 2026, 9:57 p.m.