Triple

T21399047
Position Surface form Disambiguated ID Type / Status
Subject Florence E527861 entity
Predicate associatedWith P37 FINISHED
Object city of Florence, Italy 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: city of Florence, Italy | Statement: [Florence, associatedWith, city of Florence, Italy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Florence, Italy
Context triple: [Florence, associatedWith, city of Florence, Italy]
  • A. city of Lucca
    The city of Lucca is a historic Tuscan city in central Italy, renowned for its well-preserved Renaissance walls, medieval architecture, and rich cultural heritage.
  • 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. 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 kind, sensible young girl and one of the main human characters in the classic stop-motion children's television series "The Magic Roundabout."
  • E. Florence
    Florence is a critically acclaimed interactive story and mobile video game that explores the emotional journey of a young woman's first love through minimalist gameplay and visual storytelling.
  • 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_69e0b520ee3c8190abddbee7e37e834c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69ee62cf3e808190847ad66d2e65f9f2 completed April 26, 2026, 7:09 p.m.
Created at: April 16, 2026, 5:14 p.m.