Triple

T318124
Position Surface form Disambiguated ID Type / Status
Subject Bavaria E7752 entity
Predicate containsCity P294 FINISHED
Object Nuremberg E13122 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: Nuremberg | Statement: [Bavaria, containsCity, Nuremberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nuremberg
Context triple: [Bavaria, containsCity, 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. 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.
  • C. 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.
  • D. Dresden
    Dresden is a historic cultural and economic center in eastern Germany, renowned for its baroque architecture, art collections, and reconstruction after World War II.
  • E. Ulm
    Ulm is a historic city in the German state of Baden-Württemberg, best known for its towering Gothic cathedral and as the birthplace of physicist Albert Einstein.
  • 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_69a2e7e7af7881908890039d6be4e9b8 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ea67b7588190be394a56498758b6 completed Feb. 28, 2026, 1:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac117dd454819088a00f42e8c2af8a completed March 7, 2026, 11:52 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.