Triple

T16636461
Position Surface form Disambiguated ID Type / Status
Subject Ros E404216 entity
Predicate relatedName P3889 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: [Ros, relatedName, Rosa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rosa
Context triple: [Ros, relatedName, 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. Rosa
    Rosa is the birth name of Linda Christian, a Mexican film actress known as the first "Bond girl" for her role in the 1954 television adaptation of Casino Royale.
  • C. Rosa
    Rosa is a celebrated poem by Nikki Giovanni that honors civil rights icon Rosa Parks and reflects on the broader struggle for racial justice.
  • D. Rosa
    "Rosa" is a song by Belgian singer-songwriter Jacques Brel, known for its poetic lyrics and emotive, theatrical style characteristic of his chanson repertoire.
  • E. Rosa
    "Rosa" is a novella by Cynthia Ozick that follows a Holocaust survivor grappling with trauma, memory, and identity in postwar America.
  • 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_69d8838a41f08190b0c3f79c47df5078 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e378ea4b848190bf7c95dad8a855f0 completed April 18, 2026, 12:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a007dc28df48190b01c1328df24df60 completed May 10, 2026, 12:44 p.m.
Created at: April 10, 2026, 5:17 a.m.