Triple

T18446074
Position Surface form Disambiguated ID Type / Status
Subject Hija de la fortuna E450661 entity
Predicate mainCharacter P1183 FINISHED
Object Joaquín Andieta 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: Joaquín Andieta | Statement: [Hija de la fortuna, mainCharacter, Joaquín Andieta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joaquín Andieta
Context triple: [Hija de la fortuna, mainCharacter, Joaquín Andieta]
  • A. Joaquín Andieta chosen
    Joaquín Andieta is a passionate young Chilean revolutionary and love interest in Isabel Allende’s novel "Daughter of Fortune."
  • B. Silvino Lobos
    Silvino Lobos is a rural municipality in the province of Northern Samar in the Philippines, known for its mountainous terrain and largely agricultural economy.
  • C. Armando Barillo
    Armando Barillo is a powerful Mexican drug lord and primary antagonist in the action film "Once Upon a Time in Mexico."
  • D. Alfredo Rojo
    Alfredo Rojo is an individual notable enough to be recognized as a prominent bearer of the surname Rojo.
  • E. Mariano Álvarez
    Mariano Álvarez was a prominent Filipino revolutionary figure who played a key role in organizing and leading resistance against Spanish colonial rule in the late 19th century.
  • 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_69d8d38345688190b565eac2e4cd7935 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e51c15127881909d23b6dd45d7ccc9 completed April 19, 2026, 6:16 p.m.
Created at: April 10, 2026, 11:30 a.m.