Triple

T3242978
Position Surface form Disambiguated ID Type / Status
Subject Saskia as Flora E68004 entity
Predicate depicts P1581 FINISHED
Object Flora E201351 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: [Saskia as Flora, depicts, Flora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Flora
Context triple: [Saskia as Flora, depicts, Flora]
  • A. Flora chosen
    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
    Flora is the middle name of Ruth Disney, the daughter of Walt Disney and his wife Lillian.
  • D. Hyacinth
    Hyacinth is a given name of Greek origin, historically associated with mythological and floral imagery and used for people of any gender.
  • E. Petaloudes
    Petaloudes is a picturesque valley on the island of Rhodes in Greece, famous for its seasonal swarms of colorful butterflies that attract many visitors.
  • 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_69ad858e4c708190aa31d486cfee8a6a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaf17463481909447f6ab46016407 completed March 8, 2026, 5:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b27757dff0819081a26aea52ede49d completed March 12, 2026, 8:20 a.m.
Created at: March 8, 2026, 3:08 p.m.