Triple
T408123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Konrad Adenauer |
E9425
|
entity |
| Predicate | residence |
P75
|
FINISHED |
| Object | Rhöndorf |
E52804
|
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: Rhöndorf | Statement: [Konrad Adenauer, residence, Rhöndorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rhöndorf Context triple: [Konrad Adenauer, residence, Rhöndorf]
-
A.
Rhöndorf
chosen
Rhöndorf is a district of Bad Honnef in Germany, best known as the longtime residence and final home of the first Chancellor of the Federal Republic of Germany, Konrad Adenauer.
-
B.
Lommersweiler
Lommersweiler is a village and municipal section of the town of St. Vith in the German-speaking Community of eastern Belgium.
-
C.
Büllingen
Büllingen is a municipality in eastern Belgium’s German-speaking Community, known for its rural landscape and proximity to the historically significant Elsenborn Ridge.
-
D.
Boblingen
Böblingen is a town in the German state of Baden-Württemberg, known for its automotive industry presence and proximity to Stuttgart.
-
E.
Lichtenfels
Lichtenfels is a town in the Upper Franconia region of Bavaria, Germany, known for its basket-making tradition and historic architecture.
- 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_69a2e80111fc8190961d5b7c6154123f |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ecbf0650819080753815ca280eec |
completed | Feb. 28, 2026, 1:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a42a12e5548190aedc6e18ef24c0ce |
completed | March 1, 2026, 11:59 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.