Triple

T16975216
Position Surface form Disambiguated ID Type / Status
Subject Bamberg Bahnhof E411791 entity
Predicate connectsTo P845 FINISHED
Object Hof
Hof is a town in northern Bavaria, Germany, known as a regional transport hub and former textile and industrial center near the Czech border.
 E230925 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: Hof | Statement: [Bamberg Bahnhof, connectsTo, Hof]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hof
Context triple: [Bamberg Bahnhof, connectsTo, Hof]
  • A. Hof
    Hof is a small settlement within the municipality of Lutzenberg in the Swiss canton of Appenzell Ausserrhoden.
  • B. Hof
    Hof is a town in northeastern Bavaria, Germany, known for its location near the Czech border and its regional cultural and economic significance.
  • C. Heiderhof
    Heiderhof is a residential subdistrict of the Bonn borough Bad Godesberg in western Germany.
  • D. Planegg
    Planegg is a municipality in the district of Munich in Bavaria, Germany, known for its scenic location along the Würm River and its proximity to the city of Munich.
  • E. Hever
    Hever is a village in Kent, England, best known as the location of the historic Hever Castle, former childhood home of Anne Boleyn.
  • 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: Hof
Triple: [Bamberg Bahnhof, connectsTo, Hof]
Generated description
Hof is a town in northern Bavaria, Germany, known as a regional transport hub and former textile and industrial center near the Czech border.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hof
Target entity description: Hof is a town in northern Bavaria, Germany, known as a regional transport hub and former textile and industrial center near the Czech border.
  • A. Hof chosen
    Hof is a town in northeastern Bavaria, Germany, known for its location near the Czech border and its regional cultural and economic significance.
  • B. Hof
    Hof is a small settlement within the municipality of Lutzenberg in the Swiss canton of Appenzell Ausserrhoden.
  • C. Heiderhof
    Heiderhof is a residential subdistrict of the Bonn borough Bad Godesberg in western Germany.
  • D. Planegg
    Planegg is a municipality in the district of Munich in Bavaria, Germany, known for its scenic location along the Würm River and its proximity to the city of Munich.
  • E. Hever
    Hever is a village in Kent, England, best known as the location of the historic Hever Castle, former childhood home of Anne Boleyn.
  • F. None of above.

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_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d18300c8819080c8bf19962754ba completed April 18, 2026, 6:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00d4755ffc8190a5c861462e33d526 completed May 10, 2026, 6:54 p.m.
NEDg Description generation batch_6a00d687aed88190915e20e8fa517a2b completed May 10, 2026, 7:03 p.m.
NED2 Entity disambiguation (via description) batch_6a00d6ecbf60819095e3f8418a84d485 completed May 10, 2026, 7:05 p.m.
Created at: April 10, 2026, 5:31 a.m.