Triple

T14995545
Position Surface form Disambiguated ID Type / Status
Subject Yalitza Aparicio E373950 entity
Predicate familyName P18 FINISHED
Object Aparicio
Aparicio is a Spanish-language surname borne by various notable individuals across fields such as film, sports, and politics.
 E1133720 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: Aparicio | Statement: [Yalitza Aparicio, familyName, Aparicio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Aparicio
Context triple: [Yalitza Aparicio, familyName, Aparicio]
  • A. Carabajal
    Carabajal is a Spanish-origin surname, often considered a variant of Carvajal, borne by various families across Spain and Latin America.
  • B. Vásquez
    Vásquez is a Spanish-language surname common in Latin America and Spain, borne by numerous notable figures in sports, politics, and the arts.
  • C. Herrero
    Herrero is a Spanish occupational surname derived from the word for "blacksmith" or "smith."
  • D. Montúfar
    Montúfar is a Spanish-origin surname historically associated with notable figures in Latin American colonial and independence-era history.
  • E. Velasco
    Velasco is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
  • 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: Aparicio
Triple: [Yalitza Aparicio, familyName, Aparicio]
Generated description
Aparicio is a Spanish-language surname borne by various notable individuals across fields such as film, sports, and politics.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Aparicio
Target entity description: Aparicio is a Spanish-language surname borne by various notable individuals across fields such as film, sports, and politics.
  • A. Carabajal
    Carabajal is a Spanish-origin surname, often considered a variant of Carvajal, borne by various families across Spain and Latin America.
  • B. Vásquez
    Vásquez is a Spanish-language surname common in Latin America and Spain, borne by numerous notable figures in sports, politics, and the arts.
  • C. Herrero
    Herrero is a Spanish occupational surname derived from the word for "blacksmith" or "smith."
  • D. Montúfar
    Montúfar is a Spanish-origin surname historically associated with notable figures in Latin American colonial and independence-era history.
  • E. Velasco
    Velasco is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
  • 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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded718e4288190b5e144f82299a194 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9dc7f4b48190b95af06d443fa37c completed May 9, 2026, 2:36 a.m.
NEDg Description generation batch_69fea0791f1c81908dcad401fa3ac245 completed May 9, 2026, 2:48 a.m.
NED2 Entity disambiguation (via description) batch_69fea11a35a88190a5ad6f261fd2d9dc completed May 9, 2026, 2:51 a.m.
Created at: April 10, 2026, 2:53 a.m.