Triple
T8337663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hattingen |
E195827
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Holthausen
Holthausen is a district of the German town of Hattingen in North Rhine-Westphalia.
|
E744536
|
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: Holthausen | Statement: [Hattingen, hasSubdivision, Holthausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Holthausen Context triple: [Hattingen, hasSubdivision, Holthausen]
-
A.
Griesheim
Griesheim is a town in the German state of Hesse, located near the city of Darmstadt and known for its residential character and local industry.
-
B.
Rottweil
Rottweil is a historic town in southwestern Germany known for its medieval architecture and as the namesake of the Rottweiler dog breed.
-
C.
Borgholzhausen
Borgholzhausen is a small town in North Rhine-Westphalia, Germany, known for its location on the Teutoburg Forest and its historical ties to the former County of Ravensberg.
-
D.
Albershausen
Albershausen is a small municipality in the German state of Baden-Württemberg, located in the Göppingen district in southern Germany.
-
E.
Herrenberg
Herrenberg is a historic town in the German state of Baden-Württemberg, known for its well-preserved medieval center and proximity to the Schönbuch Nature Park.
- 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: Holthausen Triple: [Hattingen, hasSubdivision, Holthausen]
Generated description
Holthausen is a district of the German town of Hattingen in North Rhine-Westphalia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Holthausen Target entity description: Holthausen is a district of the German town of Hattingen in North Rhine-Westphalia.
-
A.
Griesheim
Griesheim is a town in the German state of Hesse, located near the city of Darmstadt and known for its residential character and local industry.
-
B.
Rottweil
Rottweil is a historic town in southwestern Germany known for its medieval architecture and as the namesake of the Rottweiler dog breed.
-
C.
Borgholzhausen
Borgholzhausen is a small town in North Rhine-Westphalia, Germany, known for its location on the Teutoburg Forest and its historical ties to the former County of Ravensberg.
-
D.
Albershausen
Albershausen is a small municipality in the German state of Baden-Württemberg, located in the Göppingen district in southern Germany.
-
E.
Herrenberg
Herrenberg is a historic town in the German state of Baden-Württemberg, known for its well-preserved medieval center and proximity to the Schönbuch Nature Park.
- 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_69ca82ecbdc481908a55cad8ca062d88 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7fd5027c81909724f25aa30bbe58 |
completed | March 31, 2026, 8:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cea805b8bc8190924dcf2ab51ba1e7 |
completed | April 2, 2026, 5:31 p.m. |
| NEDg | Description generation | batch_69cea994f0ac819092fb34a0f2357611 |
completed | April 2, 2026, 5:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ceaa4c7ba08190be86cccc3a857656 |
completed | April 2, 2026, 5:41 p.m. |
Created at: March 30, 2026, 5:57 p.m.