Triple

T8572016
Position Surface form Disambiguated ID Type / Status
Subject Selzach E202947 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: [Selzach, partOf, Lebern District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lebern District
Context triple: [Selzach, 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. Neustadt district
    Neustadt district is a vibrant urban quarter of Dresden, Germany, known for its historic architecture, lively cultural scene, and diverse nightlife.
  • 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_69ca8327b0a881908606ff860713964d completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbea43843c8190ac2224d427bb7a75 completed March 31, 2026, 3:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69d05bdc87fc8190a5ae0883742cb08c completed April 4, 2026, 12:31 a.m.
Created at: March 30, 2026, 6:21 p.m.