Triple
T8797353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oberursel (Taunus) |
E209321
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object |
Oberstedten
Oberstedten is a district of the town Oberursel in Hesse, Germany, situated near the Taunus mountain range.
|
E797625
|
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: Oberstedten | Statement: [Oberursel (Taunus), hasDistrict, Oberstedten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oberstedten Context triple: [Oberursel (Taunus), hasDistrict, Oberstedten]
-
A.
Weiterstadt
Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
-
B.
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.
-
C.
Herzogenaurach
Herzogenaurach is a Bavarian town in Germany best known as the birthplace and headquarters of the global sportswear brands Adidas and Puma.
-
D.
Kulmbach
Kulmbach is a historic Bavarian town in northern Germany renowned for its beer brewing tradition and its hilltop Plassenburg Castle.
-
E.
Hettstadt
Hettstadt is a small municipality in the Würzburg district of Bavaria, Germany, known for its rural character and proximity to the city of Würzburg.
- 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: Oberstedten Triple: [Oberursel (Taunus), hasDistrict, Oberstedten]
Generated description
Oberstedten is a district of the town Oberursel in Hesse, Germany, situated near the Taunus mountain range.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Oberstedten Target entity description: Oberstedten is a district of the town Oberursel in Hesse, Germany, situated near the Taunus mountain range.
-
A.
Weiterstadt
Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
-
B.
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.
-
C.
Herzogenaurach
Herzogenaurach is a Bavarian town in Germany best known as the birthplace and headquarters of the global sportswear brands Adidas and Puma.
-
D.
Kulmbach
Kulmbach is a historic Bavarian town in northern Germany renowned for its beer brewing tradition and its hilltop Plassenburg Castle.
-
E.
Hettstadt
Hettstadt is a small municipality in the Würzburg district of Bavaria, Germany, known for its rural character and proximity to the city of Würzburg.
- 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_69ca836240888190a62b262e56a69d2f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fa370d08190885ef65e3a3e56d3 |
completed | March 31, 2026, 11:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d10771c3288190860875ebcc12103e |
completed | April 4, 2026, 12:43 p.m. |
| NEDg | Description generation | batch_69d1086f03808190896186daa5857e39 |
completed | April 4, 2026, 12:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1090215308190beda7c0115020f5b |
completed | April 4, 2026, 12:50 p.m. |
Created at: March 30, 2026, 6:44 p.m.