Triple

T13343520
Position Surface form Disambiguated ID Type / Status
Subject Cristina Banegas E317886 entity
Predicate familyName P18 FINISHED
Object Banegas
Banegas is a Spanish-language surname borne by various notable individuals in the arts, sports, and public life across Latin America and Spain.
 E1035585 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: Banegas | Statement: [Cristina Banegas, familyName, Banegas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Banegas
Context triple: [Cristina Banegas, familyName, Banegas]
  • A. Gachalá
    Gachalá is a small Colombian town in the Cundinamarca Department, known for its emerald mining and scenic Andean landscapes.
  • B. Báguanos
    Báguanos is a municipality in eastern Cuba located in the province of Holguín, known for its agricultural activities and rural communities.
  • C. Bañuela
    Bañuela is the highest peak in Spain’s Sierra Morena mountain range, located in the southern part of the Iberian Peninsula.
  • D. Narón
    Narón is a municipality in the province of A Coruña in Galicia, northwestern Spain, known for its close ties to the nearby city of Ferrol and its role in the region’s industrial and service economy.
  • E. Barcaság
    Barcaság is the Hungarian name for Burzenland, a historic region in southeastern Transylvania, Romania, known for its medieval Saxon heritage and fortified towns.
  • 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: Banegas
Triple: [Cristina Banegas, familyName, Banegas]
Generated description
Banegas is a Spanish-language surname borne by various notable individuals in the arts, sports, and public life across Latin America and Spain.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Banegas
Target entity description: Banegas is a Spanish-language surname borne by various notable individuals in the arts, sports, and public life across Latin America and Spain.
  • A. Gachalá
    Gachalá is a small Colombian town in the Cundinamarca Department, known for its emerald mining and scenic Andean landscapes.
  • B. Báguanos
    Báguanos is a municipality in eastern Cuba located in the province of Holguín, known for its agricultural activities and rural communities.
  • C. Bañuela
    Bañuela is the highest peak in Spain’s Sierra Morena mountain range, located in the southern part of the Iberian Peninsula.
  • D. Narón
    Narón is a municipality in the province of A Coruña in Galicia, northwestern Spain, known for its close ties to the nearby city of Ferrol and its role in the region’s industrial and service economy.
  • E. Barcaság
    Barcaság is the Hungarian name for Burzenland, a historic region in southeastern Transylvania, Romania, known for its medieval Saxon heritage and fortified towns.
  • 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_69d806b5a3c08190b42c267fb092f98a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99e8839b48190b164414b418e756c completed April 11, 2026, 1:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f71f417e4081908ab2025a313bfad1 completed May 3, 2026, 10:11 a.m.
NEDg Description generation batch_69f7204ac36c8190a04e921442489e9c completed May 3, 2026, 10:15 a.m.
NED2 Entity disambiguation (via description) batch_69f7221887208190ac98945a023bc496 completed May 3, 2026, 10:23 a.m.
Created at: April 9, 2026, 9:31 p.m.