Triple

T9585951
Position Surface form Disambiguated ID Type / Status
Subject Mauricio E231289 entity
Predicate hasVariant P455 FINISHED
Object Mauro
Mauro is a masculine given name, common in Italian and Spanish-speaking countries, derived from the Latin name Maurus.
 E809080 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: Mauro | Statement: [Mauricio, hasVariant, Mauro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mauro
Context triple: [Mauricio, hasVariant, Mauro]
  • A. Aroldo
    Aroldo is a lesser-known opera by Italian composer Giuseppe Verdi, adapted from his earlier work Stiffelio and set in medieval England and Scotland.
  • B. Silvano
    Silvano is an Italian given name, related to Silvio, traditionally associated with the Latin name Silvanus meaning "of the forest" or "woodland."
  • C. Roberto
    Roberto is a masculine given name commonly used in Romance-language countries, equivalent to the English name Robert.
  • D. 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.
  • E. Marcio
    Marcio is a masculine given name commonly used in Portuguese- and Spanish-speaking countries, derived from the Latin name Marcius.
  • 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: Mauro
Triple: [Mauricio, hasVariant, Mauro]
Generated description
Mauro is a masculine given name, common in Italian and Spanish-speaking countries, derived from the Latin name Maurus.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mauro
Target entity description: Mauro is a masculine given name, common in Italian and Spanish-speaking countries, derived from the Latin name Maurus.
  • A. Aroldo
    Aroldo is a lesser-known opera by Italian composer Giuseppe Verdi, adapted from his earlier work Stiffelio and set in medieval England and Scotland.
  • B. Silvano
    Silvano is an Italian given name, related to Silvio, traditionally associated with the Latin name Silvanus meaning "of the forest" or "woodland."
  • C. Roberto
    Roberto is a masculine given name commonly used in Romance-language countries, equivalent to the English name Robert.
  • D. 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.
  • E. Marcio
    Marcio is a masculine given name commonly used in Portuguese- and Spanish-speaking countries, derived from the Latin name Marcius.
  • 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_69ca848161688190a68d514a0a9d5129 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd99edc2c08190b67b40f6214d46f1 completed April 1, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1617cd02c8190a1efbeb5bad0e48e completed April 4, 2026, 7:07 p.m.
NEDg Description generation batch_69d1624400b8819085b1c1a93cddc3f6 completed April 4, 2026, 7:11 p.m.
NED2 Entity disambiguation (via description) batch_69d162b39c888190ae71b05ee2e132a8 completed April 4, 2026, 7:12 p.m.
Created at: March 30, 2026, 8:06 p.m.