Triple

T17591166
Position Surface form Disambiguated ID Type / Status
Subject Lucerne region E428450 entity
Predicate contains P35 FINISHED
Object Horw 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: Horw | Statement: [Lucerne region, contains, Horw]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Horw
Context triple: [Lucerne region, contains, Horw]
  • A. Horw chosen
    Horw is a municipality in the canton of Lucerne in central Switzerland, located on the shores of Lake Lucerne and known for its proximity to the city of Lucerne and its educational institutions.
  • B. Erwitte
    Erwitte is a small town in the German state of North Rhine-Westphalia, known for its historic architecture and location in the Soest district.
  • C. Hitdorf
    Hitdorf is a district of the German city of Leverkusen, located along the Rhine and known for its riverside residential character.
  • D. Hof
    Hof is a town in northeastern Bavaria, Germany, known for its location near the Czech border and its regional cultural and economic significance.
  • E. Hof
    Hof is a small settlement within the municipality of Lutzenberg in the Swiss canton of Appenzell Ausserrhoden.
  • 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_69d889e1030481909950e140c63255b9 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e469e6e3888190b73a5b6d7e8c0a55 completed April 19, 2026, 5:36 a.m.
Created at: April 10, 2026, 5:51 a.m.