Triple
T15969017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Oeynhausen |
E387270
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Oeynhausen
Oeynhausen is a German family name most notably associated with the spa town of Bad Oeynhausen in North Rhine-Westphalia.
|
E1241727
|
NE FINISHED |
How this triple was built (4 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: Oeynhausen | Statement: [Bad Oeynhausen, namedAfter, Oeynhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oeynhausen Context triple: [Bad Oeynhausen, namedAfter, Oeynhausen]
-
A.
Essinghausen
Essinghausen is a village and locality that forms part of the town of Peine in Lower Saxony, Germany.
-
B.
Ochsenhausen
Ochsenhausen is a small historic town in the German state of Baden-Württemberg, best known for its former Benedictine monastery, Ochsenhausen Abbey.
-
C.
Aulhausen
Aulhausen is a district of the town Rüdesheim am Rhein in the Rheingau region of Hesse, Germany, known for its scenic vineyards and rural character.
-
D.
Eppenhain
Eppenhain is a district of the town of Kelkheim in the Main-Taunus region of Hesse, Germany, known for its proximity to the Taunus hills and forested surroundings.
-
E.
Nennhausen
Nennhausen is a rural municipality in the Havelland district of Brandenburg, Germany, known for its historic manor house and surrounding natural landscapes.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Oeynhausen Triple: [Bad Oeynhausen, namedAfter, Oeynhausen]
Generated description
Oeynhausen is a German family name most notably associated with the spa town of Bad Oeynhausen in North Rhine-Westphalia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Oeynhausen Target entity description: Oeynhausen is a German family name most notably associated with the spa town of Bad Oeynhausen in North Rhine-Westphalia.
-
A.
Essinghausen
Essinghausen is a village and locality that forms part of the town of Peine in Lower Saxony, Germany.
-
B.
Ochsenhausen
Ochsenhausen is a small historic town in the German state of Baden-Württemberg, best known for its former Benedictine monastery, Ochsenhausen Abbey.
-
C.
Aulhausen
Aulhausen is a district of the town Rüdesheim am Rhein in the Rheingau region of Hesse, Germany, known for its scenic vineyards and rural character.
-
D.
Eppenhain
Eppenhain is a district of the town of Kelkheim in the Main-Taunus region of Hesse, Germany, known for its proximity to the Taunus hills and forested surroundings.
-
E.
Nennhausen
Nennhausen is a rural municipality in the Havelland district of Brandenburg, Germany, known for its historic manor house and surrounding natural landscapes.
- F. None of above. chosen
Provenance (5 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_6a00cfb95b348190a006f699c01e85ce |
completed | May 10, 2026, 6:34 p.m. |
| NEDg | Description generation | batch_6a00d0e1650881909eacc90cf99787f4 |
completed | May 10, 2026, 6:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00d1e024e88190bfcb50b42f37949b |
completed | May 10, 2026, 6:43 p.m. |
Created at: April 10, 2026, 4:54 a.m.