Triple

T2644916
Position Surface form Disambiguated ID Type / Status
Subject Y Tu Mamá También E62960 entity
Predicate producer P490 FINISHED
Object Bertha Navarro E69637 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: Bertha Navarro | Statement: [Y Tu Mamá También, producer, Bertha Navarro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bertha Navarro
Context triple: [Y Tu Mamá También, producer, Bertha Navarro]
  • A. Bertha Navarro chosen
    Bertha Navarro is a Mexican film producer best known for her long-time collaboration with director Guillermo del Toro on acclaimed genre and art-house films.
  • B. Dolores Olmedo
    Dolores Olmedo was a Mexican businesswoman, art collector, and patron best known for preserving and promoting the work of Frida Kahlo and Diego Rivera through her extensive collection and museum initiatives.
  • C. Bertha Puga Martínez
    Bertha Puga Martínez was the wife of Colombian statesman and three-time president Alberto Lleras Camargo.
  • D. Mildred García
    Mildred García is an American academic leader and administrator who serves as chancellor of the California State University system.
  • E. Inés Mendoza
    Inés Mendoza was a Puerto Rican educator and political figure who served as First Lady of Puerto Rico and was known for her advocacy of Spanish-language education.
  • 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_69ab4c3f2dcc819082df80f5e032f690 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abd917192081908e7a2cf780a17b83 completed March 7, 2026, 7:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69b055b28ad88190a9fafc15871afa5f completed March 10, 2026, 5:32 p.m.
Created at: March 6, 2026, 9:53 p.m.