Triple

T6475294
Position Surface form Disambiguated ID Type / Status
Subject Endenich campus E146055 entity
Predicate district P2709 FINISHED
Object Endenich E203710 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: Endenich | Statement: [Endenich campus, district, Endenich]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Endenich
Context triple: [Endenich campus, district, Endenich]
  • A. Endenich chosen
    Endenich is a district of Bonn, Germany, historically known as the place where composer Robert Schumann spent his final years and died in a mental asylum.
  • B. Niendorf
    Niendorf is a residential district in the northwestern part of Hamburg, Germany, known for its suburban character and proximity to Hamburg Airport.
  • C. Ilkenau
    Ilkenau is the historical German name for the Polish town of Olkusz, located in southern Poland.
  • D. Eulachstadt
    Eulachstadt is a nickname for the Swiss city of Winterthur, reflecting its historical association with the Eulach River and its development as an important industrial and cultural center.
  • E. Hohne
    Hohne is a village in Lower Saxony, Germany, historically notable for its military garrison and association with British Army units.
  • 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_69c008fec7408190af7b146dc63d9750 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a341360819082f2b5496a1a68b0 completed March 22, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c65fd1db288190b00ba6d7f3aae925 completed March 27, 2026, 10:45 a.m.
Created at: March 22, 2026, 4:50 p.m.