Triple

T18128442
Position Surface form Disambiguated ID Type / Status
Subject Transport in Bavaria E433943 entity
Predicate hasMajorHub P164 FINISHED
Object Nuremberg 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: Nuremberg | Statement: [Transport in Bavaria, hasMajorHub, Nuremberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nuremberg
Context triple: [Transport in Bavaria, hasMajorHub, Nuremberg]
  • A. Nuremberg chosen
    Nuremberg is a historic city in Bavaria, Germany, known for its medieval architecture and its role as the site of the post–World War II war crimes tribunals.
  • B. Regensburg
    Regensburg is a historic city in southeastern Germany known for its well-preserved medieval old town on the Danube River.
  • C. Munich
    Munich is the capital and largest city of the German state of Bavaria, renowned for its rich cultural scene, historic architecture, and the annual Oktoberfest beer festival.
  • D. Munich
    "Munich" is a 2005 historical drama thriller film directed by Steven Spielberg that depicts the covert Israeli response to the 1972 Munich Olympics massacre.
  • E. Weimar
    Weimar is a historic German city renowned as a center of culture and the arts, associated with figures like Goethe and Schiller and pivotal movements in modern design and architecture.
  • 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_69d8b909e8cc81908df4cc2b8ea6d11f completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ddf061b48190b67356f1c266b80a completed April 19, 2026, 1:51 p.m.
Created at: April 10, 2026, 10:29 a.m.