Triple

T18682021
Position Surface form Disambiguated ID Type / Status
Subject UN E456755 entity
Predicate region P40 FINISHED
Object District of Unna 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: District of Unna | Statement: [UN, region, District of Unna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: District of Unna
Context triple: [UN, region, District of Unna]
  • A. Regen District
    Regen District is an administrative district in the Bavarian Forest region of Bavaria, Germany, known for its wooded landscapes and proximity to the Czech border.
  • B. district of Unna chosen
    The district of Unna is an administrative district in the German state of North Rhine-Westphalia, situated in the eastern Ruhr area and encompassing several towns and municipalities including Lünen.
  • C. Senec District
    Senec District is an administrative district in western Slovakia, known for its rapidly developing suburban areas and popular recreational lakes near the capital city of Bratislava.
  • D. Lunan District
    Lunan District is an urban administrative district within the city of Tangshan in Hebei Province, China.
  • E. Van Aken District
    Van Aken District is a mixed-use urban hub in Shaker Heights, Ohio, featuring shops, restaurants, offices, and residential spaces centered around the city’s historic transit corridor.
  • 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_69d8d391eb488190ac2e9abf5bf255e4 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e55b2906ec8190ad8db8e3ae6b2945 completed April 19, 2026, 10:46 p.m.
Created at: April 10, 2026, 11:49 a.m.