Triple

T23341064
Position Surface form Disambiguated ID Type / Status
Subject Gounod’s Roméo et Juliette E591734 entity
Predicate character P662 FINISHED
Object Roméo 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: Roméo | Statement: [Gounod’s Roméo et Juliette, character, Roméo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roméo
Context triple: [Gounod’s Roméo et Juliette, character, Roméo]
  • A. Roméo chosen
    Roméo is a masculine given name of Latin origin, commonly used in French and other Romance languages and best known from Shakespeare’s tragic hero in "Romeo and Juliet."
  • B. Romeo
    Romeo is a small statutory town located in Conejos County in southern Colorado, United States.
  • C. Romeo
    Romeo is a tough, wisecracking Orbital Drop Shock Trooper and member of the Rookie’s squad in the video game Halo 3: ODST.
  • D. Romeo
    Romeo is the song that represented the host nation at the Eurovision Song Contest in 1986.
  • E. Romeo
    Romeo is a recurring mad-scientist villain in the children's animated superhero series PJ Masks, known for his inventive gadgets and schemes to outsmart the heroes.
  • 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_69e25d20e3d08190bcede87673cafb25 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f198329d9c8190992627afa9b54bed completed April 29, 2026, 5:33 a.m.
Created at: April 17, 2026, 5:18 p.m.