Triple

T16975218
Position Surface form Disambiguated ID Type / Status
Subject Bamberg Bahnhof E411791 entity
Predicate connectsTo P845 FINISHED
Object Forchheim NE NERFINISHED

How this triple was built (2 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: Forchheim | Statement: [Bamberg Bahnhof, connectsTo, Forchheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Forchheim
Context triple: [Bamberg Bahnhof, connectsTo, Forchheim]
  • A. Forchheim chosen
    Forchheim is a town in Upper Franconia, Bavaria, Germany, known for its historic old town and location along major regional rail and road routes.
  • B. Haßfurt
    Haßfurt is a small town in northern Bavaria, Germany, situated on the Main River and known for its historic architecture and regional administrative role.
  • C. Ochsenfurt
    Ochsenfurt is a historic Bavarian town in southern Germany situated on the Main River, known for its medieval architecture and wine-growing tradition.
  • D. Burghausen
    Burghausen is a historic Bavarian town in southeastern Germany, renowned for its remarkably well-preserved medieval old town and one of the longest castle complexes in the world.
  • E. Aschaffenburg
    Aschaffenburg is a historic Bavarian city in Germany known for its riverside setting on the Main, its prominent Schloss Johannisburg castle, and its role as a regional cultural and economic center.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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.
Created at: April 10, 2026, 5:31 a.m.