Triple

T15563117
Position Surface form Disambiguated ID Type / Status
Subject Gastón Gaudio E371046 entity
Predicate givenName P17 FINISHED
Object Gastón
Gastón is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
 E1163544 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: Gastón | Statement: [Gastón Gaudio, givenName, Gastón]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gastón
Context triple: [Gastón Gaudio, givenName, Gastón]
  • A. Néstor
    Néstor is a masculine given name of Spanish origin, commonly used in Spanish-speaking countries.
  • B. Humberto
    Humberto is a masculine given name of Spanish and Portuguese origin, commonly used in Iberian and Latin American countries.
  • C. Eduardo Luis
    Eduardo Luis is an actor known for playing the character Trash.
  • D. Hugo Montenegro
    Hugo Montenegro was an American composer, arranger, and conductor best known for his film and television scores and his popular orchestral cover versions of movie themes.
  • E. Héctor Julio Páride Bernabó
    Héctor Julio Páride Bernabó, better known as Carybé, was an Argentine-Brazilian painter, illustrator, and sculptor renowned for his vivid depictions of Afro-Brazilian culture and the city of Salvador, Bahia.
  • 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: Gastón
Triple: [Gastón Gaudio, givenName, Gastón]
Generated description
Gastón is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gastón
Target entity description: Gastón is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
  • A. Néstor
    Néstor is a masculine given name of Spanish origin, commonly used in Spanish-speaking countries.
  • B. Humberto
    Humberto is a masculine given name of Spanish and Portuguese origin, commonly used in Iberian and Latin American countries.
  • C. Eduardo Luis
    Eduardo Luis is an actor known for playing the character Trash.
  • D. Hugo Montenegro
    Hugo Montenegro was an American composer, arranger, and conductor best known for his film and television scores and his popular orchestral cover versions of movie themes.
  • E. Héctor Julio Páride Bernabó
    Héctor Julio Páride Bernabó, better known as Carybé, was an Argentine-Brazilian painter, illustrator, and sculptor renowned for his vivid depictions of Afro-Brazilian culture and the city of Salvador, Bahia.
  • 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04ddc66448190948280fb0c8d390c completed April 16, 2026, 2:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff456821988190971539b683f6c656 completed May 9, 2026, 2:32 p.m.
NEDg Description generation batch_69ff46f44b2c81909f65f0ab455c6549 completed May 9, 2026, 2:38 p.m.
NED2 Entity disambiguation (via description) batch_69ff477a63b48190a453cf669dfda228 completed May 9, 2026, 2:40 p.m.
Created at: April 10, 2026, 4:09 a.m.