Triple

T11939876
Position Surface form Disambiguated ID Type / Status
Subject La Guajira Department E284146 entity
Predicate hasMunicipality P847 FINISHED
Object Fonseca E878423 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: Fonseca | Statement: [La Guajira Department, hasMunicipality, Fonseca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fonseca
Context triple: [La Guajira Department, hasMunicipality, Fonseca]
  • A. Fonseca chosen
    Fonseca is a common Spanish and Portuguese surname borne by various notable figures in politics, arts, and sports across the Iberian Peninsula and Latin America.
  • B. Sercial
    Sercial is a white grape variety best known for producing the driest style of Madeira wine, characterized by high acidity and delicate, nutty citrus flavors.
  • C. Fernandes
    Fernandes is a common Portuguese surname, often patronymic in origin and widely found in Portugal, Brazil, and other Lusophone communities.
  • D. Ferrera
    Ferrera is a Spanish-origin surname most prominently associated with American actress and producer America Ferrera.
  • E. Fiquet
    Fiquet is a French surname most notably borne by Hortense Fiquet, the model and wife of painter Paul Cézanne.
  • 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_69d6ab2ce9c48190b5d39511b524f666 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903415d2481909d84e6727454b9fe completed April 10, 2026, 2:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69f4409a40dc81909d87c50601b98b78 completed May 1, 2026, 5:56 a.m.
Created at: April 8, 2026, 9:45 p.m.