Triple

T20602194
Position Surface form Disambiguated ID Type / Status
Subject Imperial Abbey of Werden E506211 entity
Predicate locatedIn P40 FINISHED
Object Werden 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: Werden | Statement: [Imperial Abbey of Werden, locatedIn, Werden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Werden
Context triple: [Imperial Abbey of Werden, locatedIn, Werden]
  • A. Werden chosen
    Werden is a historic district of the German city of Essen, known for its old town charm and the former Benedictine abbey that now houses the Folkwang University of the Arts.
  • B. Worden
    Worden is the surname of Alfred M. Worden, the American astronaut who served as the command module pilot for NASA's Apollo 15 mission.
  • C. Werdet
    Werdet was a 19th-century French publisher known for issuing works by prominent authors such as Honoré de Balzac.
  • D. Welver
    Welver is a municipality in the German state of North Rhine-Westphalia, situated in the Soest district within the historic region of Westphalia.
  • E. Gweru
    Gweru is a central Zimbabwean city that serves as the capital of the Midlands Province and an important commercial and transportation hub.
  • 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_69e0b4ba6ae88190af871e1f9522c704 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6aa20f5c881909265ce7d96efc487 completed April 20, 2026, 10:35 p.m.
Created at: April 16, 2026, 11:41 a.m.