Triple

T8789838
Position Surface form Disambiguated ID Type / Status
Subject Inning am Ammersee E209134 entity
Predicate hasSubdivision P747 FINISHED
Object Stegen
Stegen is a small village in Bavaria, Germany, situated on the shores of the Ammersee and known for its lakeside recreation and boating.
 E757772 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: Stegen | Statement: [Inning am Ammersee, hasSubdivision, Stegen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Stegen
Context triple: [Inning am Ammersee, hasSubdivision, Stegen]
  • A. Stedum
    Stedum is a small village in the province of Groningen in the Netherlands, known for its historic Romanesque church and rural setting.
  • B. Stutterheim
    Stutterheim is a small town in South Africa’s Eastern Cape province, known for its forestry, agriculture, and scenic setting near the Amathole Mountains.
  • C. Gestel
    Gestel is a district in the Dutch city of Eindhoven, located in the province of North Brabant.
  • D. Staaken
    Staaken is a locality in western Berlin, Germany, known for its residential areas and historical role as part of the Spandau district near the former inner-German border.
  • E. Stegesund
    Stegesund is a small island in the Stockholm archipelago of Sweden, known for its scenic coastal setting and proximity to the town of Vaxholm.
  • 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: Stegen
Triple: [Inning am Ammersee, hasSubdivision, Stegen]
Generated description
Stegen is a small village in Bavaria, Germany, situated on the shores of the Ammersee and known for its lakeside recreation and boating.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Stegen
Target entity description: Stegen is a small village in Bavaria, Germany, situated on the shores of the Ammersee and known for its lakeside recreation and boating.
  • A. Stedum
    Stedum is a small village in the province of Groningen in the Netherlands, known for its historic Romanesque church and rural setting.
  • B. Stutterheim
    Stutterheim is a small town in South Africa’s Eastern Cape province, known for its forestry, agriculture, and scenic setting near the Amathole Mountains.
  • C. Gestel
    Gestel is a district in the Dutch city of Eindhoven, located in the province of North Brabant.
  • D. Staaken
    Staaken is a locality in western Berlin, Germany, known for its residential areas and historical role as part of the Spandau district near the former inner-German border.
  • E. Stegesund
    Stegesund is a small island in the Stockholm archipelago of Sweden, known for its scenic coastal setting and proximity to the town of Vaxholm.
  • 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_69ca836168108190bb43d3dc235c1f55 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5f8d25f881908863d636fa57a8a2 completed March 31, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf5210454c8190aa83d941893a4bc5 completed April 3, 2026, 5:37 a.m.
NEDg Description generation batch_69cf5378c3f48190a4180c20aecb2260 completed April 3, 2026, 5:43 a.m.
NED2 Entity disambiguation (via description) batch_69cf5471e9c08190963b7f1d6c2ceffe completed April 3, 2026, 5:47 a.m.
Created at: March 30, 2026, 6:43 p.m.