Triple

T20206368
Position Surface form Disambiguated ID Type / Status
Subject Bodenseekreis E493361 entity
Predicate hasMunicipality P847 FINISHED
Object Stetten
Stetten is a small municipality in the Bodenseekreis district of the German state of Baden-Württemberg, near Lake Constance.
E1422875 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: Stetten | Statement: [Bodenseekreis, hasMunicipality, Stetten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stetten
Context triple: [Bodenseekreis, hasMunicipality, Stetten]
  • A. Stetten
    Stetten is a locality within the town of Lichtenfels in the German state of Bavaria.
  • B. Feldstetten
    Feldstetten is a village in the Swabian Alb region of Baden-Württemberg, Germany, that forms part of the town of Laichingen.
  • C. Niederstetten
    Niederstetten is a small town in the Main-Tauber district of Baden-Württemberg, Germany, known for its rural setting and historic architecture.
  • D. Altstetten
    Altstetten is a district of the city of Zurich in Switzerland, known as a major residential and transport hub in the Limmat Valley region.
  • E. Hirschstetten
    Hirschstetten is a residential and partly industrial neighborhood in Vienna, Austria, known for its local gardens and suburban character within the district of Donaustadt.
  • 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: Stetten
Triple: [Bodenseekreis, hasMunicipality, Stetten]
Generated description
Stetten is a small municipality in the Bodenseekreis district of the German state of Baden-Württemberg, near Lake Constance.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Stetten
Target entity description: Stetten is a small municipality in the Bodenseekreis district of the German state of Baden-Württemberg, near Lake Constance.
  • A. Stetten
    Stetten is a locality within the town of Lichtenfels in the German state of Bavaria.
  • B. Feldstetten
    Feldstetten is a village in the Swabian Alb region of Baden-Württemberg, Germany, that forms part of the town of Laichingen.
  • C. Niederstetten
    Niederstetten is a small town in the Main-Tauber district of Baden-Württemberg, Germany, known for its rural setting and historic architecture.
  • D. Altstetten
    Altstetten is a district of the city of Zurich in Switzerland, known as a major residential and transport hub in the Limmat Valley region.
  • E. Hirschstetten
    Hirschstetten is a residential and partly industrial neighborhood in Vienna, Austria, known for its local gardens and suburban character within the district of Donaustadt.
  • 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_69da6269614c8190bb40475d9d477358 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66d922ebc8190ae012da8ceba74dd completed April 20, 2026, 6:16 p.m.
NED1 Entity disambiguation (via context triple) batch_6a085a13ad708190bcbc91babdc4085b completed May 16, 2026, 11:50 a.m.
NEDg Description generation batch_6a085c72c81c8190bbe3c42b5832900c completed May 16, 2026, noon
NED2 Entity disambiguation (via description) batch_6a085cea59008190904995df11f6578d completed May 16, 2026, 12:02 p.m.
Created at: April 11, 2026, 11:38 p.m.