Triple

T20580426
Position Surface form Disambiguated ID Type / Status
Subject Doña Bárbara E505636 entity
Predicate hasAdaptation P1690 FINISHED
Object Doña Bárbara (telenovela) 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: Doña Bárbara (telenovela) | Statement: [Doña Bárbara, hasAdaptation, Doña Bárbara (telenovela)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Doña Bárbara (telenovela)
Context triple: [Doña Bárbara, hasAdaptation, Doña Bárbara (telenovela)]
  • A. Doña Bárbara chosen
    Doña Bárbara is a classic Venezuelan novel by Rómulo Gallegos that explores the clash between civilization and barbarism on the country’s rural plains through the figure of a ruthless female landowner.
  • B. La Reina del Sur (telenovela)
    La Reina del Sur is a Spanish-language crime drama telenovela centered on the rise of Teresa Mendoza from a poor young woman to a powerful international drug trafficker.
  • C. Angélica
    Angélica is a feminine given name of Romance-language origin, commonly used in Spanish- and Portuguese-speaking countries.
  • D. Carmencita
    Carmencita is a Spanish feminine given name, commonly used as an affectionate diminutive of Carmen.
  • E. Las Rosas
    Las Rosas is a Madrid Metro station serving the Las Rosas neighborhood in the San Blas-Canillejas district of Madrid, Spain.
  • 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_69e0b4b9669c8190b8e81fc72817d42c completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a90dd3e881908915debe1f1e8509 completed April 20, 2026, 10:30 p.m.
Created at: April 16, 2026, 11:39 a.m.