Triple

T295977
Position Surface form Disambiguated ID Type / Status
Subject Guillermo del Toro E6092 entity
Predicate hasChild P369 FINISHED
Object Mariana del Toro E38371 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: Mariana del Toro | Statement: [Guillermo del Toro, hasChild, Mariana del Toro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mariana del Toro
Context triple: [Guillermo del Toro, hasChild, Mariana del Toro]
  • A. Marisa del Toro chosen
    Marisa del Toro is one of the children of acclaimed Mexican filmmaker Guillermo del Toro.
  • B. Lolita Pulido
    Lolita Pulido is the spirited young Californio noblewoman who serves as Don Diego Vega’s love interest in Johnston McCulley’s Zorro stories, notably in "The Mark of Zorro."
  • C. Vanessa Tolosa
    Vanessa Tolosa is a biomedical engineer and neurotechnology researcher known for her work on implantable brain–computer interface devices and contributions to companies like Neuralink.
  • D. Jenny Martinez
    Jenny Martinez is an American legal scholar and former dean of Stanford Law School who serves as the provost of Stanford University.
  • E. Miriam Nicado García
    Miriam Nicado García is a Cuban mathematician and academic who became the first woman to serve as rector of the University of Havana.
  • 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_69a2e79114b081909490b3bf5a5dbb51 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2e979663481908cf9622e59fed041 completed Feb. 28, 2026, 1:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3dd2a946881909c7a53f3c712e0e3 completed March 1, 2026, 6:31 a.m.
Created at: Feb. 28, 2026, 1:06 p.m.