Triple
T16108946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siegtal |
E390818
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Hennef (Sieg) |
E375903
|
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: Hennef (Sieg) | Statement: [Siegtal, hasSettlement, Hennef (Sieg)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hennef (Sieg) Context triple: [Siegtal, hasSettlement, Hennef (Sieg)]
-
A.
Hennef (Sieg)
chosen
Hennef (Sieg) is a town in North Rhine-Westphalia, Germany, located near Bonn and known for its scenic setting along the river Sieg.
-
B.
Hennef
Hennef is a town in North Rhine-Westphalia, Germany, situated on the river Sieg near Bonn and known for its mix of residential areas, industry, and surrounding countryside.
-
C.
Raunheim
Raunheim is a town in the German state of Hesse, located near Frankfurt am Main and known for its proximity to major transportation routes and Frankfurt Airport.
-
D.
Bergisch Neukirchen
Bergisch Neukirchen is a district of the German city of Leverkusen, located in North Rhine-Westphalia.
-
E.
Gummersbach
Gummersbach is a town in North Rhine-Westphalia, Germany, known as a regional center in the Bergisches Land and a location for higher education and industry.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e20165aa9c81908c5358cca2b0d0fe |
completed | April 17, 2026, 9:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffeba674788190a589104cf90f28d5 |
completed | May 10, 2026, 2:21 a.m. |
Created at: April 10, 2026, 5 a.m.