Triple

T1034327
Position Surface form Disambiguated ID Type / Status
Subject Gustaf E22324 entity
Predicate hasSpellingVariant P457 FINISHED
Object Gustavo
Gustavo is a masculine given name commonly used in Spanish- and Portuguese-speaking countries, equivalent to the name Gustaf.
 E146523 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: Gustavo | Statement: [Gustaf, hasSpellingVariant, Gustavo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gustavo
Context triple: [Gustaf, hasSpellingVariant, Gustavo]
  • A. Jorge
    Jorge is the birth name of Pope Francis, the head of the Roman Catholic Church and the first pope from the Americas.
  • B. Sebastián
    Sebastián is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
  • 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. Raúl
    Raúl is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
  • E. Eduardo
    Eduardo is a masculine given name commonly used in Spanish and Portuguese-speaking countries, equivalent to the English name Edward.
  • 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: Gustavo
Triple: [Gustaf, hasSpellingVariant, Gustavo]
Generated description
Gustavo is a masculine given name commonly used in Spanish- and Portuguese-speaking countries, equivalent to the name Gustaf.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gustavo
Target entity description: Gustavo is a masculine given name commonly used in Spanish- and Portuguese-speaking countries, equivalent to the name Gustaf.
  • A. Jorge
    Jorge is the birth name of Pope Francis, the head of the Roman Catholic Church and the first pope from the Americas.
  • B. Sebastián
    Sebastián is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
  • 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. Raúl
    Raúl is a masculine given name of Spanish origin commonly used in Spanish-speaking countries.
  • E. Eduardo
    Eduardo is a masculine given name commonly used in Spanish and Portuguese-speaking countries, equivalent to the English name Edward.
  • 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_69a493d848848190aed4011b34b2e8d3 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b814c16c8190ac4d20feecdadbae completed March 1, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69aca2d9c98481909141f7f8ad9b8c1d completed March 7, 2026, 10:12 p.m.
NEDg Description generation batch_69aca391037c8190b6f256fcd1ac882e completed March 7, 2026, 10:15 p.m.
NED2 Entity disambiguation (via description) batch_69aca42e7c74819089666f4940ea6d4d completed March 7, 2026, 10:18 p.m.
Created at: March 1, 2026, 7:41 p.m.