Triple

T22837893
Position Surface form Disambiguated ID Type / Status
Subject Díaz E565994 entity
Predicate accentedForm P32687 FINISHED
Object Díaz 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: Díaz | Statement: [Díaz, accentedForm, Díaz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Díaz
Context triple: [Díaz, accentedForm, Díaz]
  • A. Díaz chosen
    Díaz is a common Spanish surname borne by numerous notable figures in politics, arts, and sports across the Spanish-speaking world.
  • B. Altamirano
    Altamirano is a municipality in the Mexican state of Chiapas known for its significant Indigenous Tzeltal population and role in regional social and political movements.
  • C. Díaz Vélez
    Díaz Vélez is a Spanish-language surname most notably associated with Argentine military and political figure Eustaquio Díaz Vélez.
  • D. Doroteo
    Doroteo is the given name of Doroteo Guamuch Flores, a renowned Guatemalan long-distance runner and Boston Marathon champion.
  • E. Federico Díaz
    Federico Díaz is a contemporary Czech-Argentinian artist known for his large-scale, technology-driven installations that often incorporate robotics, data, and viewer interaction.
  • 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_69e245869e188190a196584f36e682da completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17e8244dc819089c0a7525fb512ab completed April 29, 2026, 3:44 a.m.
Created at: April 17, 2026, 3:35 p.m.