Triple

T10519864
Position Surface form Disambiguated ID Type / Status
Subject Bretten E248135 entity
Predicate hasSubdivision P747 FINISHED
Object Diedelsheim
Diedelsheim is a district of the town of Bretten in the state of Baden-Württemberg in southwestern Germany.
E868538 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: Diedelsheim | Statement: [Bretten, hasSubdivision, Diedelsheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Diedelsheim
Context triple: [Bretten, hasSubdivision, Diedelsheim]
  • A. Döllersheim
    Döllersheim was a small Austrian village in Lower Austria, later depopulated and incorporated into a military training area, historically noted as the ancestral home region of Adolf Hitler’s family.
  • B. Marlenheim
    Marlenheim is a commune in northeastern France’s Alsace region, known as a historic wine-producing village and gateway to the area’s renowned vineyards and scenic countryside.
  • C. Dornheim
    Dornheim is a small village in Thuringia, Germany, historically noted as the place where Johann Sebastian Bach married Maria Barbara Bach.
  • D. Erolzheim
    Erolzheim is a small municipality in the district of Biberach in the German state of Baden-Württemberg.
  • E. Zeilsheim
    Zeilsheim is a western district of Frankfurt am Main, Germany, known for its residential character and post-war history, including a former displaced persons camp.
  • 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: Diedelsheim
Triple: [Bretten, hasSubdivision, Diedelsheim]
Generated description
Diedelsheim is a district of the town of Bretten in the state of Baden-Württemberg in southwestern Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Diedelsheim
Target entity description: Diedelsheim is a district of the town of Bretten in the state of Baden-Württemberg in southwestern Germany.
  • A. Döllersheim
    Döllersheim was a small Austrian village in Lower Austria, later depopulated and incorporated into a military training area, historically noted as the ancestral home region of Adolf Hitler’s family.
  • B. Marlenheim
    Marlenheim is a commune in northeastern France’s Alsace region, known as a historic wine-producing village and gateway to the area’s renowned vineyards and scenic countryside.
  • C. Dornheim
    Dornheim is a small village in Thuringia, Germany, historically noted as the place where Johann Sebastian Bach married Maria Barbara Bach.
  • D. Erolzheim
    Erolzheim is a small municipality in the district of Biberach in the German state of Baden-Württemberg.
  • E. Zeilsheim
    Zeilsheim is a western district of Frankfurt am Main, Germany, known for its residential character and post-war history, including a former displaced persons camp.
  • 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_69d381c4aa948190942e1d803143fb0e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509de0b3081909bec337aa8ff193e completed April 7, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d90e063e948190b2f7cbae05d9ea61 completed April 10, 2026, 2:49 p.m.
NEDg Description generation batch_69d9107dc8448190998c4044f68a775e completed April 10, 2026, 3 p.m.
NED2 Entity disambiguation (via description) batch_69d911e7d2dc8190a67b2513607fdf98 completed April 10, 2026, 3:06 p.m.
Created at: April 6, 2026, 12:28 p.m.