Triple

T15094754
Position Surface form Disambiguated ID Type / Status
Subject Lucrezia Tornabuoni E360509 entity
Predicate activeIn P1560 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: [Lucrezia Tornabuoni, activeIn, Florence]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Florence
Context triple: [Lucrezia Tornabuoni, activeIn, Florence]
  • A. Florence chosen
    Florence is a historic Italian city renowned as the cradle of the Renaissance, celebrated for its art, architecture, and cultural influence.
  • B. Florence
    Florence is a city in northwestern Alabama known as part of the Muscle Shoals metropolitan area and for its rich musical and cultural heritage.
  • C. Florence
    Florence is a small coastal city in western Oregon known for its scenic beaches, sand dunes, and historic Old Town along the Siuslaw River.
  • D. Florence
    Florence is a central character in James Baldwin's novel "Go Tell It on the Mountain," known as John Grimes's strong-willed, embittered aunt whose life story reveals the burdens of race, gender, and family in early 20th-century America.
  • E. Florence
    Florence is a neighborhood in South Los Angeles known for its dense urban character, diverse working-class community, and proximity to major transportation corridors.
  • 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0054571a48190a57055c0d6e90f82 completed April 15, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed31fa31c8190a22a27f5572e4334 completed May 9, 2026, 6:24 a.m.
Created at: April 10, 2026, 3:04 a.m.