Triple

T1794578
Position Surface form Disambiguated ID Type / Status
Subject Montserrat Caballé E39574 entity
Predicate familyName P18 FINISHED
Object Caballé E39574 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: Caballé | Statement: [Montserrat Caballé, familyName, Caballé]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caballé
Context triple: [Montserrat Caballé, familyName, Caballé]
  • A. Montserrat Caballé chosen
    Montserrat Caballé was a renowned Spanish operatic soprano celebrated for her powerful yet delicate voice and exceptional bel canto technique.
  • B. José Carreras
    José Carreras is a renowned Spanish operatic tenor, famous as one of the Three Tenors and celebrated for his performances in the Italian and French lyric repertoire.
  • C. Alberto Iglesias
    Alberto Iglesias is an acclaimed Spanish film composer known for his evocative scores for directors such as Pedro Almodóvar and for multiple Academy Award–nominated soundtracks.
  • D. Juan José Carrera
    Juan José Carrera was a Chilean independence leader and military figure, known as one of the prominent Carrera brothers who played a key role in Chile’s early struggle for emancipation from Spanish rule.
  • E. Maribel Verdú
    Maribel Verdú is a Spanish actress acclaimed for her work in films such as "Pan’s Labyrinth" and "Y Tu Mamá También."
  • 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_69a88631854081909723959921e45c2b completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa653daa0c8190a5d96c20c8a0af15 completed March 6, 2026, 5:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69adbf54330c81908046b519a0297760 completed March 8, 2026, 6:26 p.m.
Created at: March 4, 2026, 7:32 p.m.