Triple

T3336719
Position Surface form Disambiguated ID Type / Status
Subject German-speaking Switzerland E70155 entity
Predicate includesCanton P5501 FINISHED
Object Lucerne E31684 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: Lucerne | Statement: [German-speaking Switzerland, includesCanton, Lucerne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lucerne
Context triple: [German-speaking Switzerland, includesCanton, Lucerne]
  • A. Lucerne chosen
    Lucerne is a picturesque Swiss city known for its preserved medieval architecture, lakeside setting on Lake Lucerne, and proximity to the Swiss Alps.
  • B. Alsike
    Alsike is a small locality in Uppsala County, Sweden, known as a growing residential community within Knivsta Municipality.
  • C. Rhoose
    Rhoose is a coastal village in the Vale of Glamorgan in South Wales, known for its proximity to Cardiff Airport and views over the Bristol Channel.
  • D. Cynara
    Cynara is a genus of thistle-like flowering plants best known for including the cultivated artichoke.
  • E. Galega
    Galega is a small genus of flowering legumes in the pea family, best known for the species Galega officinalis, historically used as a medicinal plant and as a forage crop.
  • 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_69ad85a24f208190bcf83131bfed3521 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb1bad97481909359e914d44a1a74 completed March 8, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69b325191a38819095cdccca8f013774 completed March 12, 2026, 8:42 p.m.
Created at: March 8, 2026, 3:12 p.m.