Triple

T804474
Position Surface form Disambiguated ID Type / Status
Subject Rosa Parks E17197 entity
Predicate givenName P17 FINISHED
Object Rosa E14716 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: Rosa | Statement: [Rosa Parks, givenName, Rosa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rosa
Context triple: [Rosa Parks, givenName, Rosa]
  • A. Rosa chosen
    Rosa is a genus of flowering plants known for its ornamental roses, prized worldwide for their beauty, fragrance, and cultural symbolism.
  • B. Roses
    "Roses" is a soulful, introspective hip-hop track by Kanye West from his critically acclaimed album "Late Registration," reflecting on family, illness, and faith.
  • C. Blume
    Blume is the family name of acclaimed English actress Claire Bloom, known for her work in film, television, and theatre.
  • D. Rose in Bloom
    Rose in Bloom is a coming-of-age novel by Louisa May Alcott that follows the personal and moral development of a young heiress navigating love, family, and social expectations.
  • E. Irises
    Irises is a famous 1889 oil painting by Vincent van Gogh depicting a vibrant cluster of blooming irises, celebrated for its expressive color and dynamic composition.
  • 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_69a49378b9c48190adbf5f62e5b7aca1 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4aabebff08190880e4876ff58bcfe completed March 1, 2026, 9:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d83cf448190a2205cd777386833 completed March 3, 2026, 11:23 p.m.
Created at: March 1, 2026, 7:38 p.m.