Triple

T11222068
Position Surface form Disambiguated ID Type / Status
Subject Rottal-Inn E265593 entity
Predicate contains P35 FINISHED
Object Arnstorf
Arnstorf is a market town in the district of Rottal-Inn in Lower Bavaria, Germany, known for its rural character and regional commerce.
E925766 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: Arnstorf | Statement: [Rottal-Inn, contains, Arnstorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arnstorf
Context triple: [Rottal-Inn, contains, Arnstorf]
  • A. Adendorf
    Adendorf is a village-sized district within the municipality of Wachtberg in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
  • B. Lauterhofen
    Lauterhofen is a market town in Bavaria, Germany, known for its rural character and location within the Upper Palatinate region.
  • C. Gersthofen
    Gersthofen is a town in Bavaria, Germany, located just north of Augsburg and known for its industrial presence and role as a regional transport hub.
  • D. Gneixendorf
    Gneixendorf is a village and cadastral community that forms part of the city of Krems an der Donau in Lower Austria.
  • E. Allendorf
    Allendorf is a village-level subdivision of the town of Sundern in the Hochsauerland district of North Rhine-Westphalia, 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: Arnstorf
Triple: [Rottal-Inn, contains, Arnstorf]
Generated description
Arnstorf is a market town in the district of Rottal-Inn in Lower Bavaria, Germany, known for its rural character and regional commerce.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Arnstorf
Target entity description: Arnstorf is a market town in the district of Rottal-Inn in Lower Bavaria, Germany, known for its rural character and regional commerce.
  • A. Adendorf
    Adendorf is a village-sized district within the municipality of Wachtberg in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
  • B. Lauterhofen
    Lauterhofen is a market town in Bavaria, Germany, known for its rural character and location within the Upper Palatinate region.
  • C. Gersthofen
    Gersthofen is a town in Bavaria, Germany, located just north of Augsburg and known for its industrial presence and role as a regional transport hub.
  • D. Gneixendorf
    Gneixendorf is a village and cadastral community that forms part of the city of Krems an der Donau in Lower Austria.
  • E. Allendorf
    Allendorf is a village-level subdivision of the town of Sundern in the Hochsauerland district of North Rhine-Westphalia, 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_69d6aac59460819089b9848b27f57848 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8ec8fb08190b27144ab65f85957 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5d3049e788190a7caf324a4b793d2 completed April 20, 2026, 7:17 a.m.
NEDg Description generation batch_69e5d5cac9108190b7756329bfa320d3 completed April 20, 2026, 7:29 a.m.
NED2 Entity disambiguation (via description) batch_69e5d7f238cc8190a1c2dd26bdc5ff77 completed April 20, 2026, 7:38 a.m.
Created at: April 8, 2026, 9:30 p.m.