Triple
T910553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adolf Galland |
E19646
|
entity |
| Predicate | burialPlace |
P196
|
FINISHED |
| Object | Remagen, Germany |
E107474
|
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: Remagen, Germany | Statement: [Adolf Galland, burialPlace, Remagen, Germany]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Remagen, Germany Context triple: [Adolf Galland, burialPlace, Remagen, Germany]
-
A.
Remagen, Germany
chosen
Remagen, Germany is a town on the Rhine River best known for its strategically important Ludendorff Bridge, which played a key role in World War II.
-
B.
Jena
Jena is a historic university city in the German state of Thuringia, known for its role in optics, philosophy, and science.
-
C.
Spandau
Spandau is a western borough of Berlin, Germany, known for its historic old town, fortress, and role as an important residential and industrial district.
-
D.
Nuremberg
Nuremberg is a historic city in Bavaria, Germany, known for its medieval architecture and its role as the site of the post–World War II war crimes tribunals.
-
E.
Potsdam
Potsdam is a historic German city near Berlin, known for its palaces, parks, and role in major 20th-century diplomatic events.
- 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_69a4939f91a08190ba68c2c81eab90fe |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2dca5208190bc9f17cd9dd6a98f |
completed | March 1, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7cf5c4acc8190a0f72ca30f187ed1 |
completed | March 4, 2026, 6:21 a.m. |
Created at: March 1, 2026, 7:39 p.m.