Triple
T15969072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porta Westfalica |
E387271
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Bad Oeynhausen |
E387270
|
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: Bad Oeynhausen | Statement: [Porta Westfalica, locatedNear, Bad Oeynhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Oeynhausen Context triple: [Porta Westfalica, locatedNear, Bad Oeynhausen]
-
A.
Bad Oeynhausen
chosen
Bad Oeynhausen is a spa town in North Rhine-Westphalia, Germany, renowned for its thermal springs and health resorts.
-
B.
Bad Belzig
Bad Belzig is a historic spa town in the German state of Brandenburg known for its medieval castle and thermal baths.
-
C.
Bad Rappenau
Bad Rappenau is a spa town in the German state of Baden-Württemberg, known for its thermal baths and health resorts.
-
D.
Bad Rothenfelde
Bad Rothenfelde is a spa town in Lower Saxony, Germany, known for its saline springs and health resort facilities.
-
E.
Bad Honnef
Bad Honnef is a spa town on the Rhine in North Rhine-Westphalia, Germany, known for its scenic setting near the Siebengebirge hills and its historical associations with prominent political figures.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1572847f08190830e30125e829766 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbc6f4c08190b816bf6d92114ad2 |
completed | May 10, 2026, 1:13 a.m. |
Created at: April 10, 2026, 4:54 a.m.