Triple

T4117322
Position Surface form Disambiguated ID Type / Status
Subject Nuremberg–Bamberg railway E90323 entity
Predicate passesThrough P225 FINISHED
Object Forchheim E248845 NE FINISHED

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: [Nuremberg–Bamberg railway, passesThrough, Forchheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Forchheim
Context triple: [Nuremberg–Bamberg railway, passesThrough, 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. 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.
  • C. Rosenheim
    Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
  • D. Deggendorf
    Deggendorf is a town in southeastern Germany situated on the Danube River, known as a regional commercial and transportation hub near the Bavarian Forest.
  • E. Kulmbach
    Kulmbach is a historic Bavarian town in northern Germany renowned for its beer brewing tradition and its hilltop Plassenburg Castle.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69aed95c080881908125e30c5dcdc6f8 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af01f347f8819080dd250398474d7e completed March 9, 2026, 5:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfe8ba08f88190a0b10b7a0a05b98c completed March 22, 2026, 1:03 p.m.
Created at: March 9, 2026, 3:41 p.m.