Triple

T13755301
Position Surface form Disambiguated ID Type / Status
Subject Luis van Rooten E330459 entity
Predicate givenName P17 FINISHED
Object Luis
Luis van Rooten was a Panamanian-born American character actor and voice artist known for his work in mid-20th-century film, radio, and television.
 E1098594 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 van Rooten, givenName, Luis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Luis
Context triple: [Luis van Rooten, 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 van Rooten, givenName, Luis]
Generated description
Luis van Rooten was a Panamanian-born American character actor and voice artist known for his work in mid-20th-century film, radio, and television.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Luis
Target entity description: Luis van Rooten was a Panamanian-born American character actor and voice artist known for his work in mid-20th-century film, radio, and television.
  • 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 a friendly human character on Sesame Street who often interacts warmly with Big Bird and the other residents of the neighborhood.
  • C. Luis
    Luis is a common Spanish given name derived from the Germanic name Ludwig, widely used across Spanish-speaking countries.
  • D. Luis
    Luis is the Spanish given name of Louis I of Spain, an 18th-century Bourbon king who briefly ruled the country.
  • E. 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.
  • 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_69d81c573f288190aa2403d484fa3d49 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02179c948190a652cc8c586e418f completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bb05bb481909a0ad528e998fdf1 completed May 8, 2026, 3:42 a.m.
NEDg Description generation batch_69fd5d078b8081908810acb77be74b2b completed May 8, 2026, 3:48 a.m.
NED2 Entity disambiguation (via description) batch_69fd5d7e07a08190be5154674f7478fb completed May 8, 2026, 3:50 a.m.
Created at: April 9, 2026, 10:09 p.m.