Triple

T11024423
Position Surface form Disambiguated ID Type / Status
Subject Florence A. Selznick E260578 entity
Predicate givenName P17 FINISHED
Object Florence E527861 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: [Florence A. Selznick, givenName, Florence]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Florence
Context triple: [Florence A. Selznick, givenName, Florence]
  • A. 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.
  • B. Florence chosen
    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.
  • C. 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.
  • D. Florence
    Florence is the birth name of Elizabeth Arden, the pioneering Canadian-American businesswoman who founded the iconic Elizabeth Arden cosmetics brand.
  • E. Florence
    Florence is a historic Italian city renowned as the cradle of the Renaissance, celebrated for its art, architecture, and cultural influence.
  • 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_69d6aa9687448190b28d353b1b6a610e completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797bf78a48190a37b423812827d4e completed April 9, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3750917d481909e73de0bfae27827 completed April 18, 2026, 12:11 p.m.
Created at: April 8, 2026, 9:25 p.m.