Triple

T13580371
Position Surface form Disambiguated ID Type / Status
Subject Luis de Borbón y Borbón-Dos Sicilias E324396 entity
Predicate givenName P17 FINISHED
Object Luis
Luis is a male given name of Spanish origin, commonly used in Spanish-speaking countries and equivalent to the English name Louis.
 E952830 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 Borbón y Borbón-Dos Sicilias, givenName, Luis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Luis
Context triple: [Luis de Borbón y Borbón-Dos Sicilias, givenName, Luis]
  • A. Luis
    Luis is a friendly human character on Sesame Street who often interacts warmly with Big Bird and the other residents of the neighborhood.
  • B. Luis
    Luis is the Spanish given name of Louis I of Spain, an 18th-century Bourbon king who briefly ruled the country.
  • C. 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.
  • D. 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.
  • E. Luis
    Luis was a Portuguese infante and nobleman who held the title Duke of Beja in the 16th century.
  • 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 Borbón y Borbón-Dos Sicilias, givenName, Luis]
Generated description
Luis is a male given name of Spanish origin, commonly used in Spanish-speaking countries and equivalent to the English name Louis.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Luis
Target entity description: Luis is a male given name of Spanish origin, commonly used in Spanish-speaking countries and equivalent to the English name Louis.
  • A. Luis chosen
    Luis is a common Spanish given name derived from the Germanic name Ludwig, widely used across Spanish-speaking countries.
  • B. Luis
    Luis is the Spanish given name of Louis I of Spain, an 18th-century Bourbon king who briefly ruled the country.
  • C. 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.
  • D. Luis
    Luis is a friendly human character on Sesame Street who often interacts warmly with Big Bird and the other residents of the neighborhood.
  • E. Luis
    Luis was a Portuguese infante and nobleman who held the title Duke of Beja in the 16th century.
  • F. None of above.

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_69d80769100c819099111274614f5ed2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb03052088190a2b68c106059828e completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbac7a1ee88190951de590a4a07d6f completed May 6, 2026, 9:02 p.m.
NEDg Description generation batch_69fbad35be6c8190aa329fa947cbdcd9 completed May 6, 2026, 9:05 p.m.
NED2 Entity disambiguation (via description) batch_69fbae42ef2c8190b653d95de94042bc completed May 6, 2026, 9:10 p.m.
Created at: April 9, 2026, 9:48 p.m.