Triple
T22789255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bestwig |
E564062
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Olsberg |
—
|
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: Olsberg | Statement: [Bestwig, locatedNear, Olsberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Olsberg Context triple: [Bestwig, locatedNear, Olsberg]
-
A.
Olsberg
chosen
Olsberg is a small town in the Hochsauerland region of North Rhine-Westphalia, Germany, known for its scenic location in the Sauerland hills and outdoor recreation opportunities.
-
B.
Insterburg
Insterburg was a historically significant town in former East Prussia, now known as Chernyakhovsk in Russia’s Kaliningrad Oblast.
-
C.
Neustadt
Neustadt is a district of the Austrian city of Salzburg, known for its central urban character within the historic and cultural landscape of the city.
-
D.
Neustadt
Neustadt is a vibrant district of Dresden, Germany, known for its historic architecture, lively arts scene, and numerous bars, cafes, and cultural venues.
-
E.
Amsberg
Amsberg is the surname of the German noble family that became closely associated with the Dutch royal House of Orange-Nassau through Prince Claus of the Netherlands.
- 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.