Triple
T21555350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mödrath |
E531876
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Kerpen |
—
|
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: Kerpen | Statement: [Mödrath, locatedIn, Kerpen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kerpen Context triple: [Mödrath, locatedIn, Kerpen]
-
A.
Kerpen
chosen
Kerpen is a town in North Rhine-Westphalia, Germany, known as the birthplace of Formula 1 champion Michael Schumacher and for its proximity to Cologne.
-
B.
Mechernich
Mechernich is a small town in the Eifel region of North Rhine-Westphalia, Germany, known for its rural landscape and cultural landmarks such as the Bruder Klaus Field Chapel.
-
C.
Moresnet
Moresnet was a small, historically contested territory in Western Europe, known for its unique status as a neutral and later jointly administered region between larger neighboring states.
-
D.
Neunkirchen
Neunkirchen is a town in southwestern Germany known as one of the major urban centers and former industrial hubs of the state of Saarland.
-
E.
Neunkirchen
Neunkirchen is an industrial town in Austria’s Lower Austria region, known historically for its manufacturing 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_69e0c460232c81908de2c3819d17c00e |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eed2df48c88190894b6b08a5cb6390 |
completed | April 27, 2026, 3:07 a.m. |
Created at: April 16, 2026, 6:29 p.m.