Triple

T9511007
Position Surface form Disambiguated ID Type / Status
Subject Rosa, Alabama E229392 entity
Predicate hasName P744 FINISHED
Object Rosa E705708 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, Alabama, hasName, Rosa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rosa
Context triple: [Rosa, Alabama, hasName, Rosa]
  • A. Rosa
    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 song by Belgian singer-songwriter Jacques Brel, known for its poetic lyrics and emotive, theatrical style characteristic of his chanson repertoire.
  • D. Rosa chosen
    Rosa is a feminine given name of Latin origin meaning "rose," used in many languages and cultures.
  • E. 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.
  • 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_69ca84777560819084cddd999badc1aa completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9868616c8190856f89fecfa1a02e completed April 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69d13a37c7ec8190a24ae0eec76b4f67 completed April 4, 2026, 4:20 p.m.
Created at: March 30, 2026, 7:58 p.m.