Triple

T16912451
Position Surface form Disambiguated ID Type / Status
Subject Fernando E410234 entity
Predicate hasDiminutive P456 FINISHED
Object Fernandito E1077351 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: Fernandito | Statement: [Fernando, hasDiminutive, Fernandito]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fernandito
Context triple: [Fernando, hasDiminutive, Fernandito]
  • A. Fernandito chosen
    Fernandito is a Spanish diminutive form of the given name Fernand, typically used as an affectionate or familiar nickname.
  • B. O’Donojú
    O’Donojú is the surname of Juan O’Donojú, the last Spanish political chief of New Spain who played a key role in Mexico’s transition to independence.
  • C. Humberto
    Humberto is a masculine given name of Spanish and Portuguese origin, commonly used in Iberian and Latin American countries.
  • D. Gamboa
    Gamboa is a small town in Panama best known for its location along the Panama Canal and its proximity to the surrounding rainforest and canal infrastructure.
  • E. Borbalán
    Borbalán is a small coastal village within the municipality of Valle Gran Rey on the island of La Gomera in Spain’s Canary Islands.
  • 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_69d886c7b1e481908c3766dfa8c13458 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3ca3e6b9481909fbaeb0bddd7e3b2 completed April 18, 2026, 6:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c7bb4ac481909318d3d61a2d10e1 completed May 10, 2026, 6 p.m.
Created at: April 10, 2026, 5:30 a.m.