Triple

T2242060
Position Surface form Disambiguated ID Type / Status
Subject Fernando Henrique Cardoso E49418 entity
Predicate givenName P17 FINISHED
Object Henrique
Henrique is a Portuguese given name commonly used in Brazil and other Lusophone countries, equivalent to the English name Henry.
 E12956 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: Henrique | Statement: [Fernando Henrique Cardoso, givenName, Henrique]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Henrique
Context triple: [Fernando Henrique Cardoso, givenName, Henrique]
  • A. Guilherme
    Guilherme is the Portuguese form of the given name William, commonly used in Portuguese-speaking countries.
  • B. António
    António is a common Portuguese given name, notably borne by António Guterres, the Secretary-General of the United Nations.
  • C. Luís
    Luís is a common Portuguese male given name, historically associated with notable figures such as the poet Luís de Camões.
  • D. Henrique Lopes de Mendonça
    Henrique Lopes de Mendonça was a Portuguese playwright, poet, and naval officer best known for writing the lyrics to Portugal’s national anthem, “A Portuguesa.”
  • 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: Henrique
Triple: [Fernando Henrique Cardoso, givenName, Henrique]
Generated description
Henrique is a Portuguese given name commonly used in Brazil and other Lusophone countries, equivalent to the English name Henry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Henrique
Target entity description: Henrique is a Portuguese given name commonly used in Brazil and other Lusophone countries, equivalent to the English name Henry.
  • A. Guilherme
    Guilherme is the Portuguese form of the given name William, commonly used in Portuguese-speaking countries.
  • B. António
    António is a common Portuguese given name, notably borne by António Guterres, the Secretary-General of the United Nations.
  • C. Luís
    Luís is a common Portuguese male given name, historically associated with notable figures such as the poet Luís de Camões.
  • D. Henrique Lopes de Mendonça chosen
    Henrique Lopes de Mendonça was a Portuguese playwright, poet, and naval officer best known for writing the lyrics to Portugal’s national anthem, “A Portuguesa.”
  • E. Diogo
    Diogo is a masculine given name, commonly used in Portuguese-speaking countries and related to the name Diego.
  • F. None of above.

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_69a88aa979788190ad6500f1d8eee2fc completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc0c017548190a71fb4a0e2a8189f completed March 7, 2026, 6:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6b0eef98819083bede32490cba7e completed March 9, 2026, 6:39 a.m.
NEDg Description generation batch_69ae6bbccdb08190a73fd20a110219d9 completed March 9, 2026, 6:42 a.m.
NED2 Entity disambiguation (via description) batch_69ae6c3d07a08190a6221a33fd02f73e completed March 9, 2026, 6:44 a.m.
Created at: March 4, 2026, 7:47 p.m.