Triple

T12385500
Position Surface form Disambiguated ID Type / Status
Subject Erlangen-Höchstadt E295851 entity
Predicate containsMunicipality P852 FINISHED
Object Buckenhof
Buckenhof is a small municipality in the Bavarian region of Franconia in southern Germany.
 E979393 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: Buckenhof | Statement: [Erlangen-Höchstadt, containsMunicipality, Buckenhof]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Buckenhof
Context triple: [Erlangen-Höchstadt, containsMunicipality, Buckenhof]
  • A. Scheibenhof
    Scheibenhof is a locality or district that forms part of the city of Krems an der Donau in Lower Austria.
  • B. Jagdhof
    Jagdhof is a notable local landmark associated with the area of Linn, likely known for its historical or architectural significance.
  • C. Schickenhof
    Schickenhof is a small locality in Germany best known as the birthplace of Nobel Prize–winning physicist Johannes Stark.
  • D. Ruckelshaus
    Ruckelshaus is the surname of William D. Ruckelshaus, a prominent American lawyer and public official best known as the first head of the U.S. Environmental Protection Agency and a key figure in the Watergate-era "Saturday Night Massacre."
  • E. Kammerhof
    Kammerhof is a historic mining administration building and museum in Banská Štiavnica, Slovakia, showcasing the town’s rich mining heritage.
  • 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: Buckenhof
Triple: [Erlangen-Höchstadt, containsMunicipality, Buckenhof]
Generated description
Buckenhof is a small municipality in the Bavarian region of Franconia in southern Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Buckenhof
Target entity description: Buckenhof is a small municipality in the Bavarian region of Franconia in southern Germany.
  • A. Scheibenhof
    Scheibenhof is a locality or district that forms part of the city of Krems an der Donau in Lower Austria.
  • B. Jagdhof
    Jagdhof is a notable local landmark associated with the area of Linn, likely known for its historical or architectural significance.
  • C. Schickenhof
    Schickenhof is a small locality in Germany best known as the birthplace of Nobel Prize–winning physicist Johannes Stark.
  • D. Ruckelshaus
    Ruckelshaus is the surname of William D. Ruckelshaus, a prominent American lawyer and public official best known as the first head of the U.S. Environmental Protection Agency and a key figure in the Watergate-era "Saturday Night Massacre."
  • E. Kammerhof
    Kammerhof is a historic mining administration building and museum in Banská Štiavnica, Slovakia, showcasing the town’s rich mining heritage.
  • 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_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d93fbd489c819098233a111442762e completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62ac939bc819081629b9eef20c4e7 completed May 2, 2026, 4:48 p.m.
NEDg Description generation batch_69f62c7b28588190839c35c19856d16f completed May 2, 2026, 4:55 p.m.
NED2 Entity disambiguation (via description) batch_69f62e403a308190a2bba3fefc420932 completed May 2, 2026, 5:02 p.m.
Created at: April 8, 2026, 9:54 p.m.