Triple

T8655864
Position Surface form Disambiguated ID Type / Status
Subject Luis de Velasco y Aragón E205413 entity
Predicate givenName P17 FINISHED
Object Luis
Luis de Velasco y Aragón was a Spanish nobleman and colonial administrator who served as Viceroy of New Spain and later of Peru in the late 17th and early 18th centuries.
 E756038 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: Luis | Statement: [Luis de Velasco y Aragón, givenName, Luis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Luis
Context triple: [Luis de Velasco y Aragón, givenName, Luis]
  • A. Luis
    Luis is a comedic supporting character in the Marvel Cinematic Universe, best known as Scott Lang’s fast-talking friend and former cellmate in the Ant-Man films.
  • B. Luis
    Luis is the Spanish given name of Louis I of Spain, an 18th-century Bourbon king who briefly ruled the country.
  • C. Jorge
    Jorge is a character portrayed by actor Giancarlo Esposito, known for his nuanced and often intense roles in film and television.
  • D. Jorge
    Jorge is a masculine given name of Spanish and Portuguese origin, equivalent to George in English.
  • E. Jorge
    Jorge is the central character of Robert Silverberg’s science fiction novella "Born with the Dead," set in a future where the dead can be partially revived and live apart from the living.
  • 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: Luis
Triple: [Luis de Velasco y Aragón, givenName, Luis]
Generated description
Luis de Velasco y Aragón was a Spanish nobleman and colonial administrator who served as Viceroy of New Spain and later of Peru in the late 17th and early 18th centuries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Luis
Target entity description: Luis de Velasco y Aragón was a Spanish nobleman and colonial administrator who served as Viceroy of New Spain and later of Peru in the late 17th and early 18th centuries.
  • A. Luis
    Luis is the Spanish given name of Louis I of Spain, an 18th-century Bourbon king who briefly ruled the country.
  • B. Luis
    Luis is a comedic supporting character in the Marvel Cinematic Universe, best known as Scott Lang’s fast-talking friend and former cellmate in the Ant-Man films.
  • C. Jorge
    Jorge is a character portrayed by actor Giancarlo Esposito, known for his nuanced and often intense roles in film and television.
  • D. Jorge
    Jorge is a masculine given name of Spanish and Portuguese origin, equivalent to George in English.
  • E. Jorge
    Jorge is the central character of Robert Silverberg’s science fiction novella "Born with the Dead," set in a future where the dead can be partially revived and live apart from the living.
  • 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_69ca8350897c819086cde7596fbe5fe7 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc4844586081909b687e278496eefa completed March 31, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf51505cf88190ab077498e5734f39 completed April 3, 2026, 5:34 a.m.
NEDg Description generation batch_69cf524413748190b4d7fd000b99e866 completed April 3, 2026, 5:38 a.m.
NED2 Entity disambiguation (via description) batch_69cf52f305a48190b899368fcb986a65 completed April 3, 2026, 5:41 a.m.
Created at: March 30, 2026, 6:29 p.m.