Triple
T20571689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lordship of Steinfurt |
E505113
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Steinfurt |
—
|
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: Steinfurt | Statement: [Lordship of Steinfurt, locatedIn, Steinfurt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steinfurt Context triple: [Lordship of Steinfurt, locatedIn, Steinfurt]
-
A.
Steinfurt
chosen
Steinfurt is a historic town in western Germany’s North Rhine-Westphalia, known for its castle, old town, and location within the rural Münsterland region.
-
B.
Rüdinghausen
Rüdinghausen is a district of the city of Witten in North Rhine-Westphalia, Germany, characterized by its residential areas and local amenities.
-
C.
Nordhorn
Nordhorn is a town in Lower Saxony, Germany, known as the administrative center of the Grafschaft Bentheim district near the Dutch border.
-
D.
Schlettstadt
Schlettstadt, now known as Sélestat, is a historic town in the Alsace region of northeastern France noted for its medieval architecture and humanist heritage.
-
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 (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_69e0b4b721588190993ac7b0a9be2736 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a905b1288190bbad9aa14362bb97 |
completed | April 20, 2026, 10:30 p.m. |
Created at: April 16, 2026, 11:39 a.m.