Triple

T16381163
Position Surface form Disambiguated ID Type / Status
Subject Queen Margarita of Bulgaria E397808 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: [Queen Margarita of Bulgaria, givenName, Margarita]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margarita
Context triple: [Queen Margarita of Bulgaria, 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. One Margarita
    "One Margarita" is a popular country party anthem by American singer Luke Bryan, known for its laid-back beach vibe and catchy, summer-themed lyrics.
  • D. Palomas
    Palomas is a small municipality located in the Tierra de Barros comarca of the Extremadura region in western Spain.
  • E. 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.
  • 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_69d87f2880b48190ae1a9673a3bbef80 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e319dd0e0c8190812bde6a2f7d9644 completed April 18, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0035689ef08190ba980a359498ca56 completed May 10, 2026, 7:36 a.m.
Created at: April 10, 2026, 5:08 a.m.