Triple

T12988371
Position Surface form Disambiguated ID Type / Status
Subject Marianela Núñez E321828 entity
Predicate givenName P17 FINISHED
Object Marianela
Marianela is a feminine given name of Spanish origin, commonly used in Spanish-speaking countries.
 E1012641 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: Marianela | Statement: [Marianela Núñez, givenName, Marianela]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marianela
Context triple: [Marianela Núñez, givenName, Marianela]
  • A. Fortunata y Jacinta
    Fortunata y Jacinta is a classic 19th-century realist novel by Spanish author Benito Pérez Galdós that explores love, class, and social change in Madrid through the intertwined lives of two women connected to the same man.
  • B. Señora de Meirás
    Señora de Meirás was the noble title held by Carmen Polo, the wife of Spanish dictator Francisco Franco, associated with the Meirás estate in Galicia.
  • C. Julita
    Julita is a feminine given name, commonly used as a diminutive or variant of Julia in various languages and cultures.
  • D. Rosario de Mora
    Rosario de Mora is a municipality located in the San Salvador Department of El Salvador.
  • E. La Celia
    La Celia is a small municipality in western Colombia known for its rural Andean landscapes and coffee-growing traditions within the Risaralda Department.
  • 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: Marianela
Triple: [Marianela Núñez, givenName, Marianela]
Generated description
Marianela is a feminine given name of Spanish origin, commonly used in Spanish-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marianela
Target entity description: Marianela is a feminine given name of Spanish origin, commonly used in Spanish-speaking countries.
  • A. Fortunata y Jacinta
    Fortunata y Jacinta is a classic 19th-century realist novel by Spanish author Benito Pérez Galdós that explores love, class, and social change in Madrid through the intertwined lives of two women connected to the same man.
  • B. Señora de Meirás
    Señora de Meirás was the noble title held by Carmen Polo, the wife of Spanish dictator Francisco Franco, associated with the Meirás estate in Galicia.
  • C. Julita
    Julita is a feminine given name, commonly used as a diminutive or variant of Julia in various languages and cultures.
  • D. Rosario de Mora
    Rosario de Mora is a municipality located in the San Salvador Department of El Salvador.
  • E. La Celia
    La Celia is a small municipality in western Colombia known for its rural Andean landscapes and coffee-growing traditions within the Risaralda Department.
  • 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_69d8076479b8819090afce3591939cdf completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e5f47ec8190b39107bc016f9824 completed April 10, 2026, 10:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6b8f942588190b69a3067d5145182 completed May 3, 2026, 2:54 a.m.
NEDg Description generation batch_69f6b9dc31ec819093c89ff0a1ccbfa1 completed May 3, 2026, 2:58 a.m.
NED2 Entity disambiguation (via description) batch_69f6baacd7548190af5514923a0dee26 completed May 3, 2026, 3:02 a.m.
Created at: April 9, 2026, 8:42 p.m.