Triple

T8351903
Position Surface form Disambiguated ID Type / Status
Subject Wienhausen Abbey E196581 entity
Predicate locatedIn P40 FINISHED
Object Wienhausen E235487 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: Wienhausen | Statement: [Wienhausen Abbey, locatedIn, Wienhausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wienhausen
Context triple: [Wienhausen Abbey, locatedIn, Wienhausen]
  • A. Wienhausen chosen
    Wienhausen is a historic village in Lower Saxony, Germany, best known for its medieval Cistercian nunnery and well-preserved half-timbered architecture.
  • B. Waigolshausen
    Waigolshausen is a small municipality in the Schweinfurt district of Bavaria, Germany, known for its rural character and location in the Franconian region.
  • C. Hausen
    Hausen is a small suburban district of the town of Herbrechtingen in the state of Baden-Württemberg, Germany.
  • D. Fleinhausen
    Fleinhausen is a small village in Bavaria, Germany, historically noted as the birthplace of Nazi propagandist Julius Streicher.
  • E. Tussenhausen
    Tussenhausen is a municipality in the district of Unterallgäu in Bavaria, Germany, known for its rural character and small villages such as Mattsies.
  • 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_69ca82f08b348190bfb7881944bbff6f completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb8019fb308190a3edc744bd473a5b completed March 31, 2026, 8:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf27cace5c8190b871c632a075cb0a completed April 3, 2026, 2:36 a.m.
Created at: March 30, 2026, 5:59 p.m.