Triple

T13674191
Position Surface form Disambiguated ID Type / Status
Subject district of Roth E327828 entity
Predicate contains P35 FINISHED
Object Schwanstetten
Schwanstetten is a municipality in the Roth district of Bavaria, Germany, known for its residential character and proximity to the city of Nuremberg.
E1111587 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: Schwanstetten | Statement: [district of Roth, contains, Schwanstetten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schwanstetten
Context triple: [district of Roth, contains, Schwanstetten]
  • A. Badenweiler
    Badenweiler is a spa town in southwestern Germany’s Black Forest region, known for its thermal baths and as the place where Russian writer Anton Chekhov died.
  • B. Schwanau
    Schwanau is a municipality in southwestern Germany’s Baden-Württemberg region, situated near the Rhine River and the French border.
  • C. 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.
  • D. Söhnstetten
    Söhnstetten is a village in the Heidenheim district of Baden-Württemberg, Germany, known as a part of the municipality of Steinheim am Albuch on the Swabian Jura.
  • E. Höchheim
    Höchheim is a small municipality in the Rhön-Grabfeld district of northern Bavaria, Germany.
  • 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: Schwanstetten
Triple: [district of Roth, contains, Schwanstetten]
Generated description
Schwanstetten is a municipality in the Roth district of Bavaria, Germany, known for its residential character and proximity to the city of Nuremberg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Schwanstetten
Target entity description: Schwanstetten is a municipality in the Roth district of Bavaria, Germany, known for its residential character and proximity to the city of Nuremberg.
  • A. Badenweiler
    Badenweiler is a spa town in southwestern Germany’s Black Forest region, known for its thermal baths and as the place where Russian writer Anton Chekhov died.
  • B. Schwanau
    Schwanau is a municipality in southwestern Germany’s Baden-Württemberg region, situated near the Rhine River and the French border.
  • C. 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.
  • D. Söhnstetten
    Söhnstetten is a village in the Heidenheim district of Baden-Württemberg, Germany, known as a part of the municipality of Steinheim am Albuch on the Swabian Jura.
  • E. Höchheim
    Höchheim is a small municipality in the Rhön-Grabfeld district of northern Bavaria, Germany.
  • 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_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc65aab348190a6611f5765f8392d completed April 12, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdd5b543308190a86e715106641484 completed May 8, 2026, 12:23 p.m.
NEDg Description generation batch_69fdd6dd77e481908283b145acae2e9a completed May 8, 2026, 12:28 p.m.
NED2 Entity disambiguation (via description) batch_69fdd771cb188190b44d6e4903fa8f6e completed May 8, 2026, 12:30 p.m.
Created at: April 9, 2026, 9:53 p.m.