Triple
T13031692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Bentheim |
E326455
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Gronau (Westf.) |
E151149
|
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: Gronau (Westf.) | Statement: [Bad Bentheim, nearbyCity, Gronau (Westf.)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gronau (Westf.) Context triple: [Bad Bentheim, nearbyCity, Gronau (Westf.)]
-
A.
Gronau (Westf)
chosen
Gronau (Westf) is a town in North Rhine-Westphalia, Germany, near the Dutch border, known for its textile industry history and as the birthplace of rock musician Udo Lindenberg.
-
B.
Gronau
Gronau is a town in Germany historically noted as the site of a battle during the Seven Years' War.
-
C.
Göhren
Göhren is a seaside resort town on the Baltic Sea coast of Germany, located on the island of Rügen and known for its beaches and tourism.
-
D.
Gummersbach
Gummersbach is a town in North Rhine-Westphalia, Germany, known as a regional center in the Bergisches Land and a location for higher education and industry.
-
E.
Ochtrup
Ochtrup is a small town in the Münster region of North Rhine-Westphalia in western Germany, known for its textile industry and designer outlet center.
- 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_69d8076cc45c81908123123f43e69266 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97efe72348190b52fb4068f5fb829 |
completed | April 10, 2026, 10:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c123c36c8190b3fbf9cbb3b7ecf9 |
completed | May 3, 2026, 3:29 a.m. |
Created at: April 9, 2026, 8:54 p.m.