Triple

T15240770
Position Surface form Disambiguated ID Type / Status
Subject Lucca E364247 entity
Predicate near P350 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: [Lucca, near, Florence]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Florence
Context triple: [Lucca, near, 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 small coastal city in western Oregon known for its scenic beaches, sand dunes, and historic Old Town along the Siuslaw River.
  • C. 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.
  • D. Florence
    Florence is a feminine given name of Latin origin, historically associated with the meaning "prosperous" or "flourishing" and borne by numerous notable figures and places.
  • E. Florence
    Florence is a fictional character in Ali Smith's novel "Spring," playing a pivotal role in the book's exploration of contemporary politics, migration, and human connection.
  • 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_69d85a0dde7481908fc64d1e82d5d20d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007db9a148190aadea8d5f8b6b261 completed April 15, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fedd2dc6f08190a8f1612ac29a8654 completed May 9, 2026, 7:07 a.m.
Created at: April 10, 2026, 3:13 a.m.