Triple

T21399031
Position Surface form Disambiguated ID Type / Status
Subject Florence E527861 entity
Predicate relatedName P3889 FINISHED
Object Flora 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: Flora | Statement: [Florence, relatedName, Flora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Flora
Context triple: [Florence, relatedName, Flora]
  • A. Flora
    Flora is a symbolist painting by Evelyn De Morgan depicting the Roman goddess of flowers and spring in a richly allegorical, Pre-Raphaelite-inspired style.
  • B. Flora
    Flora is the young niece in Henry James's novella "The Turn of the Screw," whose eerie innocence and ambiguous relationship to the supernatural are central to the story's psychological horror.
  • C. Flora chosen
    Flora is a feminine given name of Latin origin meaning "flower," historically associated with the Roman goddess of flowers and spring.
  • D. Flora
    Flora is a popular brand of margarine and other spreadable food products owned by Upfield and marketed for heart health and everyday cooking.
  • E. Flora
    Flora is one of the three good fairies who serve as royal advisors and magical guardians in the animated children's series "Sofia the First."
  • 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.