Triple

T9173754
Position Surface form Disambiguated ID Type / Status
Subject Kronberg im Taunus E220143 entity
Predicate hasCityPart P12399 FINISHED
Object Oberhöchstadt
Oberhöchstadt is a district of the town of Kronberg im Taunus in Hesse, Germany, known for its residential character within the Taunus region.
E832419 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: Oberhöchstadt | Statement: [Kronberg im Taunus, hasCityPart, Oberhöchstadt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oberhöchstadt
Context triple: [Kronberg im Taunus, hasCityPart, Oberhöchstadt]
  • A. 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.
  • B. Eberhardzell
    Eberhardzell is a rural municipality in the district of Biberach in the German state of Baden-Württemberg.
  • C. Gerolzhofen
    Gerolzhofen is a small historic town in northern Bavaria, Germany, known for its medieval architecture and wine-growing surroundings.
  • D. Ötlingen
    Ötlingen is a village-like district of the town of Weil am Rhein in the southwestern German state of Baden-Württemberg, near the borders with France and Switzerland.
  • E. Ebersberg
    Ebersberg is a small Bavarian town and district capital east of Munich, known for its surrounding forest and traditional Upper Bavarian character.
  • 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: Oberhöchstadt
Triple: [Kronberg im Taunus, hasCityPart, Oberhöchstadt]
Generated description
Oberhöchstadt is a district of the town of Kronberg im Taunus in Hesse, Germany, known for its residential character within the Taunus region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Oberhöchstadt
Target entity description: Oberhöchstadt is a district of the town of Kronberg im Taunus in Hesse, Germany, known for its residential character within the Taunus region.
  • A. 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.
  • B. Eberhardzell
    Eberhardzell is a rural municipality in the district of Biberach in the German state of Baden-Württemberg.
  • C. Gerolzhofen
    Gerolzhofen is a small historic town in northern Bavaria, Germany, known for its medieval architecture and wine-growing surroundings.
  • D. Ötlingen
    Ötlingen is a village-like district of the town of Weil am Rhein in the southwestern German state of Baden-Württemberg, near the borders with France and Switzerland.
  • E. Ebersberg
    Ebersberg is a small Bavarian town and district capital east of Munich, known for its surrounding forest and traditional Upper Bavarian character.
  • 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_69ca83e467108190abcae6a33b3d4dad completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccbfa128d48190b54b8f95d77d81cc completed April 1, 2026, 6:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d23c8f14b081909df4eae9b2d16860 completed April 5, 2026, 10:42 a.m.
NEDg Description generation batch_69d23e6ca3908190b7ad7b932ab35ad7 completed April 5, 2026, 10:50 a.m.
NED2 Entity disambiguation (via description) batch_69d241020074819092bc2deea85a6ac0 completed April 5, 2026, 11:01 a.m.
Created at: March 30, 2026, 7:22 p.m.