Triple
T1976820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fernández |
E42933
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object |
Fernandes
Fernandes is a common Portuguese surname, often patronymic in origin and widely found in Portugal, Brazil, and other Lusophone communities.
|
E223491
|
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: Fernandes | Statement: [Fernández, hasVariant, Fernandes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fernandes Context triple: [Fernández, hasVariant, Fernandes]
-
A.
Athos Bulcão
Athos Bulcão was a Brazilian artist renowned for his modernist tile panels and public art that became iconic elements of Brasília’s architectural landscape.
-
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.
Joaquim
Joaquim is a given name used in certain languages as a variant of Saint Joachim, traditionally regarded as the father of the Virgin Mary in Christian tradition.
-
D.
Tadeu Marroco
Tadeu Marroco is a Brazilian-born business executive who serves as the chief executive officer of British American Tobacco.
-
E.
Diogo
Diogo is a masculine given name, commonly used in Portuguese-speaking countries and related to the name Diego.
- 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: Fernandes Triple: [Fernández, hasVariant, Fernandes]
Generated description
Fernandes is a common Portuguese surname, often patronymic in origin and widely found in Portugal, Brazil, and other Lusophone communities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fernandes Target entity description: Fernandes is a common Portuguese surname, often patronymic in origin and widely found in Portugal, Brazil, and other Lusophone communities.
-
A.
Athos Bulcão
Athos Bulcão was a Brazilian artist renowned for his modernist tile panels and public art that became iconic elements of Brasília’s architectural landscape.
-
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.
Joaquim
Joaquim is a given name used in certain languages as a variant of Saint Joachim, traditionally regarded as the father of the Virgin Mary in Christian tradition.
-
D.
Tadeu Marroco
Tadeu Marroco is a Brazilian-born business executive who serves as the chief executive officer of British American Tobacco.
-
E.
Diogo
Diogo is a masculine given name, commonly used in Portuguese-speaking countries and related to the name Diego.
- 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_69a8871289048190b00b0d7744b7b2b1 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb3f9a87c8190816db3888787ad76 |
completed | March 7, 2026, 5:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae0327600c8190adb057b596a84bca |
completed | March 8, 2026, 11:15 p.m. |
| NEDg | Description generation | batch_69ae03b41dcc81909b4439006bdffc64 |
completed | March 8, 2026, 11:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae0445a9608190918a7bd45b9bf999 |
completed | March 8, 2026, 11:20 p.m. |
Created at: March 4, 2026, 7:36 p.m.