Triple

T20277159
Position Surface form Disambiguated ID Type / Status
Subject Verona Villafranca Airport E503045 entity
Predicate near P350 FINISHED
Object Verona city centre 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: Verona city centre | Statement: [Verona Villafranca Airport, near, Verona city centre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Verona city centre
Context triple: [Verona Villafranca Airport, near, Verona city centre]
  • A. Verona (town)
    Verona is a suburban town in south-central Wisconsin, United States, known for its proximity to Madison and its mix of residential communities, parks, and local businesses.
  • B. Historic Centre of Verona chosen
    The Historic Centre of Verona is a UNESCO-listed medieval and Renaissance urban core in northern Italy, renowned for its well-preserved architecture, Roman remains, and cultural heritage.
  • C. Verona
    Verona is a historic city in northern Italy renowned for its well-preserved Roman architecture and its association with Shakespeare’s "Romeo and Juliet."
  • D. Verona
    Verona is a small borough in Allegheny County, Pennsylvania, situated along the Allegheny River just northeast of Pittsburgh.
  • E. Verona
    Verona is a small rural town in the Bega Valley region of New South Wales, Australia.
  • 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_69e0b4b0e79c8190bd61f22ef1329fa8 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e675e4cdfc81908c7cb4519a7d744b completed April 20, 2026, 6:52 p.m.
Created at: April 16, 2026, 10:35 a.m.