Triple

T14479532
Position Surface form Disambiguated ID Type / Status
Subject Fernando Trueba E359062 entity
Predicate familyName P18 FINISHED
Object Trueba
Trueba is a Spanish surname most notably associated with acclaimed film director and screenwriter Fernando Trueba.
E1100652 NE FINISHED

How this triple was built (4 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: Trueba | Statement: [Fernando Trueba, familyName, Trueba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Trueba
Context triple: [Fernando Trueba, familyName, Trueba]
  • A. Balbuena
    Balbuena is a metro station on Mexico City’s Line 1 serving the Balbuena neighborhood in the eastern part of the city.
  • B. Lobato
    Lobato is a Portuguese-language surname borne by various notable figures, including politicians, writers, and public personalities in Lusophone countries.
  • C. 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.
  • D. Guereda
    Guereda is a town in eastern Chad that serves as an administrative and market center in the Wadi Fira region.
  • E. Betances
    Betances is a Spanish-language surname most notably associated with Puerto Rican nationalist and abolitionist leader Ramón Emeterio Betances.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Trueba
Triple: [Fernando Trueba, familyName, Trueba]
Generated description
Trueba is a Spanish surname most notably associated with acclaimed film director and screenwriter Fernando Trueba.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Trueba
Target entity description: Trueba is a Spanish surname most notably associated with acclaimed film director and screenwriter Fernando Trueba.
  • A. Balbuena
    Balbuena is a metro station on Mexico City’s Line 1 serving the Balbuena neighborhood in the eastern part of the city.
  • B. Lobato
    Lobato is a Portuguese-language surname borne by various notable figures, including politicians, writers, and public personalities in Lusophone countries.
  • C. 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.
  • D. Guereda
    Guereda is a town in eastern Chad that serves as an administrative and market center in the Wadi Fira region.
  • E. Betances
    Betances is a Spanish-language surname most notably associated with Puerto Rican nationalist and abolitionist leader Ramón Emeterio Betances.
  • F. None of above. chosen

Provenance (5 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_69d827966698819082e140837737501d completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de924a576c819098351efabdb779b1 completed April 14, 2026, 7:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd64a257488190818c65c1cc84c4b5 completed May 8, 2026, 4:20 a.m.
NEDg Description generation batch_69fd6609ed5c8190a5d2c5fe25ea1467 completed May 8, 2026, 4:26 a.m.
NED2 Entity disambiguation (via description) batch_69fd666f81d08190a0d658b5949e0201 completed May 8, 2026, 4:28 a.m.
Created at: April 10, 2026, 1:20 a.m.