Triple

T6401966
Position Surface form Disambiguated ID Type / Status
Subject Flumenthal E144083 entity
Predicate partOf P40 FINISHED
Object Lebern District E511739 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: Lebern District | Statement: [Flumenthal, partOf, Lebern District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lebern District
Context triple: [Flumenthal, partOf, Lebern District]
  • A. Lebern District chosen
    Lebern District is an administrative district in the canton of Solothurn in northwestern Switzerland.
  • B. Mohrungen district
    Mohrungen district was a former administrative district in East Prussia, centered around the town of Mohrungen (now Morąg in Poland), that existed under German rule until the end of World War II.
  • C. Karlstein district
    Karlstein district is a neighborhood of the spa town Bad Reichenhall in Bavaria, Germany, known for its scenic Alpine setting and historic character.
  • D. Hof district
    Hof district is a rural administrative district in the Bavarian region of Upper Franconia in Germany, known for its small towns, agricultural areas, and proximity to the Czech border.
  • E. Dukenburg district
    Dukenburg district is a residential area in the southwestern part of Nijmegen, Netherlands, characterized by post-war housing estates, green spaces, and local shopping facilities.
  • 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_69c008dc56fc81908d43ffcc11d73bdd completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c068ade8c881908a0472f1de6b7c21 completed March 22, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c640bee09481908bdd0462f7cc43ff completed March 27, 2026, 8:33 a.m.
Created at: March 22, 2026, 4:35 p.m.