Triple

T3136560
Position Surface form Disambiguated ID Type / Status
Subject Alberto E65543 entity
Predicate hasVariant P455 FINISHED
Object Adalberto
Adalberto is a masculine given name of Germanic origin, commonly used in Romance-language countries as a variant of Albert or Alberto.
 E333958 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: Adalberto | Statement: [Alberto, hasVariant, Adalberto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Adalberto
Context triple: [Alberto, hasVariant, Adalberto]
  • A. Gustavo
    Gustavo is a masculine given name commonly used in Spanish- and Portuguese-speaking countries, equivalent to the name Gustaf.
  • B. 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.
  • C. Ernesto
    Ernesto is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
  • D. Juan O’Donojú
    Juan O’Donojú was a Spanish military officer and statesman who, as the final viceroy of New Spain, played a key role in negotiating Mexico’s independence from Spain in 1821.
  • E. Roberto
    Roberto is a masculine given name commonly used in Romance-language countries, equivalent to the English name Robert.
  • 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: Adalberto
Triple: [Alberto, hasVariant, Adalberto]
Generated description
Adalberto is a masculine given name of Germanic origin, commonly used in Romance-language countries as a variant of Albert or Alberto.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Adalberto
Target entity description: Adalberto is a masculine given name of Germanic origin, commonly used in Romance-language countries as a variant of Albert or Alberto.
  • A. Gustavo
    Gustavo is a masculine given name commonly used in Spanish- and Portuguese-speaking countries, equivalent to the name Gustaf.
  • B. 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.
  • C. Ernesto
    Ernesto is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
  • D. Juan O’Donojú
    Juan O’Donojú was a Spanish military officer and statesman who, as the final viceroy of New Spain, played a key role in negotiating Mexico’s independence from Spain in 1821.
  • E. Roberto
    Roberto is a masculine given name commonly used in Romance-language countries, equivalent to the English name Robert.
  • 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_69ad8581c25c8190b0d85ba9b9baa531 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada564eacc8190a54d07b4eb31c196 completed March 8, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69b235b2aa388190ae9dc569b951206d completed March 12, 2026, 3:40 a.m.
NEDg Description generation batch_69b2372a54a481908a4a954b8986aad7 completed March 12, 2026, 3:46 a.m.
NED2 Entity disambiguation (via description) batch_69b23806a3c8819096069982b3612730 completed March 12, 2026, 3:50 a.m.
Created at: March 8, 2026, 3:05 p.m.