Triple

T2072311
Position Surface form Disambiguated ID Type / Status
Subject Maurice E44841 entity
Predicate hasVariant P455 FINISHED
Object Mauricio
Mauricio is a masculine given name, commonly used in Spanish- and Portuguese-speaking countries, derived from the Latin name Mauritius.
 E231289 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: Mauricio | Statement: [Maurice, hasVariant, Mauricio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mauricio
Context triple: [Maurice, hasVariant, Mauricio]
  • A. Jorge Guillermo
    Jorge Guillermo is a Cuban-born American educator and former husband of Princess Christina of the Netherlands.
  • B. Julián Felipe
    Julián Felipe was a Filipino composer best known for writing the music of the Philippine national anthem.
  • C. Marcelo
    Marcelo is a common Portuguese and Spanish given name, notably borne by figures such as Brazilian footballer Marcelo Vieira and former Portuguese Prime Minister Marcelo Caetano.
  • D. Juan José Flores
    Juan José Flores was a Venezuelan-born military leader and statesman who became the first president of Ecuador and played a key role in the country’s early republican history.
  • E. Mariano
    Mariano is a masculine given name of Spanish and Portuguese origin, commonly used in various Spanish-speaking and Latin cultures.
  • 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: Mauricio
Triple: [Maurice, hasVariant, Mauricio]
Generated description
Mauricio is a masculine given name, commonly used in Spanish- and Portuguese-speaking countries, derived from the Latin name Mauritius.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mauricio
Target entity description: Mauricio is a masculine given name, commonly used in Spanish- and Portuguese-speaking countries, derived from the Latin name Mauritius.
  • A. Jorge Guillermo
    Jorge Guillermo is a Cuban-born American educator and former husband of Princess Christina of the Netherlands.
  • B. Julián Felipe
    Julián Felipe was a Filipino composer best known for writing the music of the Philippine national anthem.
  • C. Marcelo
    Marcelo is a common Portuguese and Spanish given name, notably borne by figures such as Brazilian footballer Marcelo Vieira and former Portuguese Prime Minister Marcelo Caetano.
  • D. Juan José Flores
    Juan José Flores was a Venezuelan-born military leader and statesman who became the first president of Ecuador and played a key role in the country’s early republican history.
  • E. Mariano
    Mariano is a masculine given name of Spanish and Portuguese origin, commonly used in various Spanish-speaking and Latin cultures.
  • 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_69a88916c2b48190a5ca2e9b12cad3ed completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abba0eaa5081908f6d6ff80f79b1c9 completed March 7, 2026, 5:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae272ee27c8190a4bb4690961dccf6 completed March 9, 2026, 1:49 a.m.
NEDg Description generation batch_69ae27b2c9d08190b1950abd8d41d3b3 completed March 9, 2026, 1:51 a.m.
NED2 Entity disambiguation (via description) batch_69ae2817ce3c81908e48170760cf98ef completed March 9, 2026, 1:53 a.m.
Created at: March 4, 2026, 7:41 p.m.