Triple

T14329304
Position Surface form Disambiguated ID Type / Status
Subject Ivana Baquero E355298 entity
Predicate familyName P18 FINISHED
Object Baquero E355298 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: Baquero | Statement: [Ivana Baquero, familyName, Baquero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baquero
Context triple: [Ivana Baquero, familyName, Baquero]
  • A. Baquero chosen
    Baquero is a Spanish surname most notably associated with actress Ivana Baquero, known for her role in the film "Pan's Labyrinth."
  • B. Vásquez
    Vásquez is a Spanish-language surname common in Latin America and Spain, borne by numerous notable figures in sports, politics, and the arts.
  • C. Gamboa
    Gamboa is a small town in Panama best known for its location along the Panama Canal and its proximity to the surrounding rainforest and canal infrastructure.
  • D. Balbuena
    Balbuena is a metro station on Mexico City’s Line 1 serving the Balbuena neighborhood in the eastern part of the city.
  • E. Quiñonez
    Quiñonez is the surname of actor Tony Revolori, known for his role in "The Grand Budapest Hotel."
  • 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_69d8278fa2108190bc0d0e7939c1eb03 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8c1def0081908f03cda8e84d20c0 completed April 14, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd46927af48190b91095d852fcacbe completed May 8, 2026, 2:12 a.m.
Created at: April 10, 2026, 1:13 a.m.