Triple

T551511
Position Surface form Disambiguated ID Type / Status
Subject Nicolás Guillén E11849 entity
Predicate givenName P17 FINISHED
Object Nicolás
Nicolás is a masculine given name of Greek origin, commonly used in Spanish-speaking countries and derived from the name Nicholas, meaning "victory of the people."
 E77168 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: Nicolás | Statement: [Nicolás Guillén, givenName, Nicolás]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nicolás
Context triple: [Nicolás Guillén, givenName, Nicolás]
  • A. Eduardo
    Eduardo is a masculine given name commonly used in Spanish and Portuguese-speaking countries, equivalent to the English name Edward.
  • B. Andrés
    Andrés is a Spanish given name commonly used as the equivalent of Andrew.
  • C. Felipe de Neve
    Felipe de Neve was an 18th-century Spanish colonial governor of California best known for establishing the city of Los Angeles.
  • D. José
    José is the given first name of Major League Baseball manager and former player Alex Cora.
  • E. Juan Manuel de Ayala
    Juan Manuel de Ayala was an 18th-century Spanish naval officer and explorer credited with one of the first European chartings of San Francisco Bay.
  • 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: Nicolás
Triple: [Nicolás Guillén, givenName, Nicolás]
Generated description
Nicolás is a masculine given name of Greek origin, commonly used in Spanish-speaking countries and derived from the name Nicholas, meaning "victory of the people."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nicolás
Target entity description: Nicolás is a masculine given name of Greek origin, commonly used in Spanish-speaking countries and derived from the name Nicholas, meaning "victory of the people."
  • A. Eduardo
    Eduardo is a masculine given name commonly used in Spanish and Portuguese-speaking countries, equivalent to the English name Edward.
  • B. Andrés
    Andrés is a Spanish given name commonly used as the equivalent of Andrew.
  • C. Felipe de Neve
    Felipe de Neve was an 18th-century Spanish colonial governor of California best known for establishing the city of Los Angeles.
  • D. José
    José is the given first name of Major League Baseball manager and former player Alex Cora.
  • E. Juan Manuel de Ayala
    Juan Manuel de Ayala was an 18th-century Spanish naval officer and explorer credited with one of the first European chartings of San Francisco Bay.
  • 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_69a4932941d08190815efd422f0b4ca7 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a499047bd4819089ca8345f1b6e46c completed March 1, 2026, 7:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69a55544eda481908fae6a9f77ff9d97 completed March 2, 2026, 9:15 a.m.
NEDg Description generation batch_69a5595a7fac8190944a6b6146623673 completed March 2, 2026, 9:33 a.m.
NED2 Entity disambiguation (via description) batch_69a559ca6c6881908451d3b024745277 completed March 2, 2026, 9:35 a.m.
Created at: March 1, 2026, 7:32 p.m.