Triple
T22789198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winterberg |
E564061
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Willingen |
—
|
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: Willingen | Statement: [Winterberg, locatedNear, Willingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Willingen Context triple: [Winterberg, locatedNear, Willingen]
-
A.
Willingen (Upland)
chosen
Willingen (Upland) is a popular resort town in the Sauerland region of Hesse, Germany, known for its winter sports, hiking opportunities, and annual ski jumping World Cup events.
-
B.
Rüttenscheid
Rüttenscheid is a lively, upscale district of Essen, Germany, known for its bustling shopping streets, restaurants, and cultural venues.
-
C.
Bergkamen
Bergkamen is a town in North Rhine-Westphalia, Germany, known for its coal mining heritage and post-war planned urban development.
-
D.
Villingen
Villingen is a historic German town in the Black Forest region, now part of the twin city of Villingen-Schwenningen in the state of Baden-Württemberg.
-
E.
Oberhäuser
Oberhäuser is a German-language surname, typically of toponymic origin, associated with people or families from places named Oberhausen or similar.
- 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_69e2455500788190b4b33030461f3bbd |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17c33be7c8190ad22391a85fa000d |
completed | April 29, 2026, 3:34 a.m. |
Created at: April 17, 2026, 3:29 p.m.