Triple

T22483199
Position Surface form Disambiguated ID Type / Status
Subject Eva Noblezada E555817 entity
Predicate notableWork P4 FINISHED
Object Yellow Rose 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: Yellow Rose | Statement: [Eva Noblezada, notableWork, Yellow Rose]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yellow Rose
Context triple: [Eva Noblezada, notableWork, Yellow Rose]
  • A. Yellow Rose chosen
    "Yellow Rose" is an independent musical drama film that follows a Filipina teen in Texas pursuing her dream of becoming a country music singer while facing the threat of deportation.
  • B. The Yellow Rose
    The Yellow Rose is an American television drama series from the early 1980s centered on a Texas ranching family.
  • C. Yellow Roses
    "Yellow Roses" is a country song best known through its rendition by Ry Cooder on his album *Chicken Skin Music*.
  • D. Yellow Rose of Texas
    The "Yellow Rose of Texas" is a popular nickname for the city of Amarillo, reflecting its association with Texas heritage and its name’s Spanish meaning of “yellow.”
  • E. Rambling Rose
    Rambling Rose is a 1991 American drama film, set in the 1930s South, for which Laura Dern received critical acclaim and an Academy Award nomination for her lead performance.
  • 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_69e11e53897c819088863779f8c50bb0 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15c3b03d881909e286a124c1a2b1c completed April 29, 2026, 1:17 a.m.
Created at: April 16, 2026, 8:49 p.m.