Triple
T20949342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reichenbachbrücke |
E515937
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Au-Haidhausen |
—
|
NE NERFINISHED |
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: Au-Haidhausen | Statement: [Reichenbachbrücke, locatedIn, Au-Haidhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Au-Haidhausen Context triple: [Reichenbachbrücke, locatedIn, Au-Haidhausen]
-
A.
Stadelhofen
Stadelhofen is a village and district of the town of Oberkirch in the Ortenau region of Baden-Württemberg, Germany.
-
B.
Haidhausen area
The Haidhausen area is a historic and now trendy district of Munich known for its charming old buildings, lively cafés, and cultural venues along the Isar River.
-
C.
Munich-Haidhausen
chosen
Munich-Haidhausen is a historic and centrally located district of Munich known for its charming old streets, vibrant cultural scene, and mix of residential and governmental buildings.
-
D.
Giesing
Giesing is a district in Munich, Germany, known as a historically working-class neighborhood that today combines residential areas with notable institutions such as the nearby Stadelheim Prison.
-
E.
Bockenheim
Bockenheim is a lively urban district of Frankfurt am Main known for its mix of residential areas, shops, and university facilities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4fcd678819087a304291f14330a |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fadc08148190b4ff710f94462a26 |
completed | April 21, 2026, 4:19 a.m. |
Created at: April 16, 2026, 1:15 p.m.