Triple

T15092334
Position Surface form Disambiguated ID Type / Status
Subject José María Amador E360450 entity
Predicate familyName P18 FINISHED
Object Amador
Amador is a Spanish surname borne by various notable individuals, including figures in Californian and Latin American history.
 E1137645 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: Amador | Statement: [José María Amador, familyName, Amador]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Amador
Context triple: [José María Amador, familyName, Amador]
  • A. Martinez
    Martinez is a common Spanish-origin surname widely borne across the Spanish-speaking world and beyond.
  • B. Peralta
    Peralta is a town in northern Spain’s Navarre region situated along the Arga River.
  • C. Moraga
    Moraga is a Spanish surname most notably associated with José Joaquín Moraga, an 18th-century Spanish military officer and explorer involved in the colonization of California.
  • D. Pacheco
    Pacheco is a Spanish surname borne by various notable figures in fields such as politics, arts, and sports.
  • E. Avellaneda
    Avellaneda is a city in the Buenos Aires Province of Argentina, known as an important industrial and port center within the Greater Buenos Aires metropolitan area.
  • 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: Amador
Triple: [José María Amador, familyName, Amador]
Generated description
Amador is a Spanish surname borne by various notable individuals, including figures in Californian and Latin American history.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Amador
Target entity description: Amador is a Spanish surname borne by various notable individuals, including figures in Californian and Latin American history.
  • A. Martinez
    Martinez is a common Spanish-origin surname widely borne across the Spanish-speaking world and beyond.
  • B. Peralta
    Peralta is a town in northern Spain’s Navarre region situated along the Arga River.
  • C. Moraga
    Moraga is a Spanish surname most notably associated with José Joaquín Moraga, an 18th-century Spanish military officer and explorer involved in the colonization of California.
  • D. Pacheco
    Pacheco is a Spanish surname borne by various notable figures in fields such as politics, arts, and sports.
  • E. Avellaneda
    Avellaneda is a city in the Buenos Aires Province of Argentina, known as an important industrial and port center within the Greater Buenos Aires metropolitan area.
  • 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0027925788190b955fdc6626adf7d completed April 15, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69feae1f406081909d4925474370da86 completed May 9, 2026, 3:46 a.m.
NEDg Description generation batch_69feb2e869808190b691d95531dc7447 completed May 9, 2026, 4:07 a.m.
NED2 Entity disambiguation (via description) batch_69feb3a61e008190aff906cae172a744 completed May 9, 2026, 4:10 a.m.
Created at: April 10, 2026, 3:04 a.m.