Triple

T16567701
Position Surface form Disambiguated ID Type / Status
Subject Edgar Rentería E402504 entity
Predicate familyName P18 FINISHED
Object Rentería
Rentería is a Spanish-language surname most notably associated with Colombian former Major League Baseball shortstop Edgar Rentería.
 E81781 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: Rentería | Statement: [Edgar Rentería, familyName, Rentería]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Rentería
Context triple: [Edgar Rentería, familyName, Rentería]
  • A. Rentería
    Rentería (Errenteria) is a town in the Basque province of Gipuzkoa in northern Spain, known for its industrial history and proximity to San Sebastián.
  • B. El Arreglito
    El Arreglito is a song by Spanish composer Sebastián Iradier whose melody later became famous worldwide as the basis for the "Habanera" aria in Bizet’s opera Carmen.
  • C. Los Pedroches
    Los Pedroches is a rural comarca in northern Córdoba, Spain, known for its extensive dehesa landscapes, holm oak forests, and Iberian pig farming.
  • D. Plateros
    Plateros is a major Catholic pilgrimage site in Zacatecas, Mexico, renowned for its sanctuary dedicated to the Santo Niño de Atocha.
  • E. Rosario de Mora
    Rosario de Mora is a municipality located in the San Salvador Department of El Salvador.
  • 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: Rentería
Triple: [Edgar Rentería, familyName, Rentería]
Generated description
Rentería is a Spanish-language surname most notably associated with Colombian former Major League Baseball shortstop Edgar Rentería.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Rentería
Target entity description: Rentería is a Spanish-language surname most notably associated with Colombian former Major League Baseball shortstop Edgar Rentería.
  • A. Rentería chosen
    Rentería (Errenteria) is a town in the Basque province of Gipuzkoa in northern Spain, known for its industrial history and proximity to San Sebastián.
  • B. El Arreglito
    El Arreglito is a song by Spanish composer Sebastián Iradier whose melody later became famous worldwide as the basis for the "Habanera" aria in Bizet’s opera Carmen.
  • C. Los Pedroches
    Los Pedroches is a rural comarca in northern Córdoba, Spain, known for its extensive dehesa landscapes, holm oak forests, and Iberian pig farming.
  • D. Plateros
    Plateros is a major Catholic pilgrimage site in Zacatecas, Mexico, renowned for its sanctuary dedicated to the Santo Niño de Atocha.
  • E. Rosario de Mora
    Rosario de Mora is a municipality located in the San Salvador Department of El Salvador.
  • F. None of above.

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_69d8838648088190acf97ef11fc3f61b completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e35772f6608190a125c7d3c199c3e2 completed April 18, 2026, 10:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a006ee3dcbc819087ea66b262585232 completed May 10, 2026, 11:41 a.m.
NEDg Description generation batch_6a006ff5bdb88190be90d7446e24b61f completed May 10, 2026, 11:45 a.m.
NED2 Entity disambiguation (via description) batch_6a007088fd988190b3dfef081769d03e completed May 10, 2026, 11:48 a.m.
Created at: April 10, 2026, 5:16 a.m.