Triple

T737436
Position Surface form Disambiguated ID Type / Status
Subject Grand Tour E14964 entity
Predicate typicalDestination P3248 FINISHED
Object Florence E26762 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: Florence | Statement: [Grand Tour, typicalDestination, Florence]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Florence
Context triple: [Grand Tour, typicalDestination, Florence]
  • A. Florence
    Florence is the birth name of Elizabeth Arden, the pioneering Canadian-American businesswoman who founded the iconic Elizabeth Arden cosmetics brand.
  • B. Florence chosen
    Florence is a historic Italian city renowned as the cradle of the Renaissance, celebrated for its art, architecture, and cultural influence.
  • C. Pisa
    Pisa is a historic Italian city in Tuscany best known for its iconic Leaning Tower and as a significant center of medieval trade, learning, and architecture.
  • D. Bologna
    Bologna is a historic city in northern Italy renowned for its medieval architecture, rich culinary tradition, and the University of Bologna, one of the oldest universities in the world.
  • E. Genoa
    Genoa is a historic port city in northwestern Italy known for its significant maritime heritage, trade, and role as a major economic hub on the Ligurian coast.
  • 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_69a4934d9930819099eed80096b0597d completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4aa9ba3888190889a1ad554f73c5e completed March 1, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac6ef9b97881908eab2a5472b02183 completed March 7, 2026, 6:31 p.m.
Created at: March 1, 2026, 7:37 p.m.