Triple

T9354865
Position Surface form Disambiguated ID Type / Status
Subject Margarita Maza de Juárez E225112 entity
Predicate givenName P17 FINISHED
Object Margarita E66654 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: Margarita | Statement: [Margarita Maza de Juárez, givenName, Margarita]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margarita
Context triple: [Margarita Maza de Juárez, givenName, Margarita]
  • A. Margarita chosen
    Margarita is a feminine given name of Spanish origin, equivalent to "Margaret" in English.
  • B. Margarita
    Margarita is a classic tequila-based cocktail typically made with lime juice and orange liqueur, often served in a salt-rimmed glass.
  • C. Palomas
    Palomas is a small municipality located in the Tierra de Barros comarca of the Extremadura region in western Spain.
  • D. Tequila and Bonetti
    Tequila and Bonetti is an early-1990s American comedy-drama television series about a New York cop partnered with a talking police dog in a California beach town.
  • E. The Bottle of Anís del Mono
    The Bottle of Anís del Mono is a famous Cubist still-life painting by Juan Gris, notable for its fragmented depiction of a popular Spanish anisette bottle.
  • 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_69ca842abfd48190949d71c3b86eeba8 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd4f99205c8190a5ad95926ef25497 completed April 1, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0e458a24881909a032553ce8a45fe completed April 4, 2026, 10:13 a.m.
Created at: March 30, 2026, 7:42 p.m.