Triple
T5852986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wernigerode |
E130080
|
entity |
| Predicate | locatedEastOf |
P4240
|
FINISHED |
| Object | Goslar |
E51097
|
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: Goslar | Statement: [Wernigerode, locatedEastOf, Goslar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Goslar Context triple: [Wernigerode, locatedEastOf, Goslar]
-
A.
Goslar
chosen
Goslar is a historic German town at the foot of the Harz Mountains, renowned for its well-preserved medieval old town and former silver mines, both recognized as UNESCO World Heritage Sites.
-
B.
Lemgo
Lemgo is a historic town in the Lippe district of North Rhine-Westphalia, Germany, known for its well-preserved medieval architecture and Hanseatic heritage.
-
C.
Boppard
Boppard is a historic town on the Rhine River in Germany, renowned for its well-preserved medieval architecture, wine culture, and scenic river landscapes.
-
D.
Meppen
Meppen is a historic town in Lower Saxony, Germany, known as a regional center in the Emsland district near the Dutch border.
-
E.
Radevormwald
Radevormwald is a small historic town in North Rhine-Westphalia, western Germany, known for its hilly Bergisches Land landscape and traditional textile and metalworking industries.
- 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_69c0084de39081909eb34e6bed74215a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0355038008190bf38980349b533e2 |
completed | March 22, 2026, 6:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0a1b8f8508190942ce1725884d254 |
completed | March 23, 2026, 2:13 a.m. |
Created at: March 22, 2026, 3:55 p.m.