Triple

T15865561
Position Surface form Disambiguated ID Type / Status
Subject Alps E384701 entity
Predicate hasCity P316 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: [Alps, hasCity, Lucerne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lucerne
Context triple: [Alps, hasCity, 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. Vetch
    Vetch is a surname most notably associated with Samuel Vetch, a colonial governor of Nova Scotia in the early 18th century.
  • C. Parsley Hay
    Parsley Hay is a small hamlet and popular cycling and walking hub in the Peak District National Park, known for its trailhead facilities on former railway routes.
  • D. Alfalfa
    Alfalfa is a beloved character from the classic "Our Gang" (later known as "The Little Rascals") comedy shorts, recognizable for his cowlick hairstyle and off-key singing.
  • E. Schildkraut
    Schildkraut is a surname most notably associated with Austrian-American actor Joseph Schildkraut, an Academy Award winner known for his work in early 20th-century film and theater.
  • 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_69d86da4e86481909f1325fdc971b5ec completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1555f75e88190bfd0f551d4ccf4cc completed April 16, 2026, 9:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa945d9808190a65f5182db341393 completed May 9, 2026, 9:38 p.m.
Created at: April 10, 2026, 4:50 a.m.