Triple

T12618274
Position Surface form Disambiguated ID Type / Status
Subject Luis de Haro E301311 entity
Predicate givenName P17 FINISHED
Object Luis
Luis is a masculine given name of Spanish origin, widely used in Spanish- and Portuguese-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 Haro, givenName, Luis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Luis
Context triple: [Luis de Haro, 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 Haro, givenName, Luis]
Generated description
Luis is a masculine given name of Spanish origin, widely used in Spanish- and Portuguese-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 masculine given name of Spanish origin, widely used in Spanish- and Portuguese-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 was a Portuguese infante and nobleman who held the title Duke of Beja in the 16th century.
  • 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 is a friendly human character on Sesame Street who often interacts warmly with Big Bird and the other residents of the neighborhood.
  • 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_69d7bdeaf49c8190b13800111fa77ea3 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d960c63ea48190ae1aae9280a023a6 completed April 10, 2026, 8:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f5b9e0c4819095194dc42677e17f completed May 3, 2026, 7:14 a.m.
NEDg Description generation batch_69f6f80b420c8190b5028be4fa99fb59 completed May 3, 2026, 7:23 a.m.
NED2 Entity disambiguation (via description) batch_69f6f89072a88190b3182f581b1b6762 completed May 3, 2026, 7:26 a.m.
Created at: April 9, 2026, 5:13 p.m.