Triple

T13594477
Position Surface form Disambiguated ID Type / Status
Subject Luis Guzmán E324779 entity
Predicate givenName P17 FINISHED
Object Luis
Luis is a common Spanish given name widely used across Spanish-speaking countries and communities.
 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 Guzmán, givenName, Luis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Luis
Context triple: [Luis Guzmán, 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 Guzmán, givenName, Luis]
Generated description
Luis is a common Spanish given name widely used across Spanish-speaking countries and communities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Luis
Target entity description: Luis is a common Spanish given name widely used across Spanish-speaking countries and communities.
  • 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 friendly human character on Sesame Street who often interacts warmly with Big Bird and the other residents of the neighborhood.
  • D. 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.
  • 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_69d80769eaf081909d82f44e484d6113 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb057f1c881909a3bb77c659a724a completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbc3138cc48190acb28a18ac9bb3eb completed May 6, 2026, 10:39 p.m.
NEDg Description generation batch_69fc4348617881908262390a447ad7af completed May 7, 2026, 7:46 a.m.
NED2 Entity disambiguation (via description) batch_69fc446397988190bb0e415680312ac0 completed May 7, 2026, 7:50 a.m.
Created at: April 9, 2026, 9:49 p.m.