Triple

T15053689
Position Surface form Disambiguated ID Type / Status
Subject Princess Marianne of Prussia E379431 entity
Predicate placeOfDeath P21 FINISHED
Object Ernstbrunn
Ernstbrunn is a market town in Lower Austria known historically as an estate center of the noble House of Kinsky.
E1143797 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: Ernstbrunn | Statement: [Princess Marianne of Prussia, placeOfDeath, Ernstbrunn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ernstbrunn
Context triple: [Princess Marianne of Prussia, placeOfDeath, Ernstbrunn]
  • A. Dittelbrunn
    Dittelbrunn is a municipality in the Schweinfurt district of Bavaria, Germany, known for its residential character and proximity to the city of Schweinfurt.
  • B. Feldbrunnen
    Feldbrunnen is a village and municipality in the canton of Solothurn in northwestern Switzerland.
  • C. Nußbach
    Nußbach is a village and district of the town of Oberkirch in the Ortenau region of Baden-Württemberg, Germany.
  • D. Groß Dölln
    Groß Dölln is a small village in Brandenburg, Germany, known for its surrounding forests, lakes, and the nearby former military airfield now used as a driving and testing center.
  • E. Breidenbach
    Breidenbach is a municipality in the German state of Hesse, known for its rural setting near the Rothaar Mountains and proximity to the town of Bad Laasphe.
  • 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: Ernstbrunn
Triple: [Princess Marianne of Prussia, placeOfDeath, Ernstbrunn]
Generated description
Ernstbrunn is a market town in Lower Austria known historically as an estate center of the noble House of Kinsky.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ernstbrunn
Target entity description: Ernstbrunn is a market town in Lower Austria known historically as an estate center of the noble House of Kinsky.
  • A. Dittelbrunn
    Dittelbrunn is a municipality in the Schweinfurt district of Bavaria, Germany, known for its residential character and proximity to the city of Schweinfurt.
  • B. Feldbrunnen
    Feldbrunnen is a village and municipality in the canton of Solothurn in northwestern Switzerland.
  • C. Nußbach
    Nußbach is a village and district of the town of Oberkirch in the Ortenau region of Baden-Württemberg, Germany.
  • D. Groß Dölln
    Groß Dölln is a small village in Brandenburg, Germany, known for its surrounding forests, lakes, and the nearby former military airfield now used as a driving and testing center.
  • E. Breidenbach
    Breidenbach is a municipality in the German state of Hesse, known for its rural setting near the Rothaar Mountains and proximity to the town of Bad Laasphe.
  • 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_69d85cd64d108190853797a95c11cc45 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69deda92091c81909180f486edf01405 completed April 15, 2026, 12:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69fed31debb48190908d59178e67adb6 completed May 9, 2026, 6:24 a.m.
NEDg Description generation batch_69fed50514b08190bc50d2e700d82e69 completed May 9, 2026, 6:32 a.m.
NED2 Entity disambiguation (via description) batch_69fed5693ff08190b16b4c8fc8bdf959 completed May 9, 2026, 6:34 a.m.
Created at: April 10, 2026, 3:01 a.m.