Triple

T14655514
Position Surface form Disambiguated ID Type / Status
Subject Bad Education E344097 entity
Predicate editedBy P1954 FINISHED
Object José Salcedo E551533 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: José Salcedo | Statement: [Bad Education, editedBy, José Salcedo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: José Salcedo
Context triple: [Bad Education, editedBy, José Salcedo]
  • A. José Salcedo chosen
    José Salcedo was a renowned Spanish film editor best known for his long-standing collaboration with director Pedro Almodóvar on numerous acclaimed films.
  • B. Juan Valeriano Zeballos
    Juan Valeriano Zeballos was a historical figure known for his active role in Paraguay’s struggle to achieve independence from colonial rule.
  • C. Manuel Ochoa
    Manuel Ochoa is a personal name shared by multiple individuals, including figures in fields such as sports, arts, and public life.
  • D. José Paciano
    José Paciano is the given first name of Jose P. Laurel, who served as President of the Philippines during the Japanese occupation in World War II.
  • E. José María Bocanegra
    José María Bocanegra was a Mexican lawyer and politician who briefly served as interim president of Mexico during the turbulent early years of the republic.
  • 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_69d822e1a2cc81908e5bb93cf61ce3cc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb51a562c819098971447db4b29f7 completed April 14, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fedd1bb1c48190b5d2b4167c756abf completed May 9, 2026, 7:07 a.m.
Created at: April 10, 2026, 1:27 a.m.