Triple

T17127573
Position Surface form Disambiguated ID Type / Status
Subject Nürnberg-Steinbühl station E415637 entity
Predicate country P26 FINISHED
Object Germany E1728 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: Germany | Statement: [Nürnberg-Steinbühl station, country, Germany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Germany
Context triple: [Nürnberg-Steinbühl station, country, Germany]
  • A. Germany chosen
    Germany is a major Central European country known for its pivotal role in 20th-century history, its strong industrial economy, and its influential contributions to science, philosophy, music, and engineering.
  • B. Saksa
    Saksa is a prominent mountain in Norway’s Sunnmøre Alps, known for its steep ascent and panoramic views over the Hjørundfjord.
  • C. Germany B
    Germany B is the secondary national football team of Germany, typically used to develop and evaluate players on the fringe of the senior national squad.
  • D. West Germany
    West Germany was the democratic, capitalist western portion of Germany during the Cold War, which became an economic powerhouse and key NATO member after World War II.
  • E. Germany and Austria
    Germany and Austria are neighboring Central European countries that share historical, cultural, and linguistic ties, including a common use of the German language.
  • 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_69d886d090cc8190a39cb94992586905 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f027a3d081908fc1134b50db3d45 completed April 18, 2026, 8:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0139f17a5481908896c1c6ff326c2f completed May 11, 2026, 2:07 a.m.
Created at: April 10, 2026, 5:36 a.m.