Triple

T16374526
Position Surface form Disambiguated ID Type / Status
Subject Flora Purim E397647 entity
Predicate givenName P17 FINISHED
Object Flora E712737 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: Flora | Statement: [Flora Purim, givenName, Flora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Flora
Context triple: [Flora Purim, givenName, 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 (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_69d87f2880b48190ae1a9673a3bbef80 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e319d6942081909616a2c6efee9967 completed April 18, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a003561f83481909223c99bb83ebdf4 completed May 10, 2026, 7:36 a.m.
Created at: April 10, 2026, 5:08 a.m.