Triple

T4293940
Position Surface form Disambiguated ID Type / Status
Subject Henrique Alvim Corrêa E99661 entity
Predicate hasGivenName P17 FINISHED
Object Henrique
Henrique is a masculine given name of Portuguese origin commonly used in Portuguese- and Spanish-speaking countries.
 E428331 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: [Henrique Alvim Corrêa, hasGivenName, Henrique]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Henrique
Context triple: [Henrique Alvim Corrêa, hasGivenName, Henrique]
  • A. Sebastião
    Sebastião is the Portuguese variant of the given name Sebastian, commonly used in Portuguese-speaking countries.
  • B. Guilherme
    Guilherme is the Portuguese form of the given name William, commonly used in Portuguese-speaking countries.
  • C. António
    António is a common Portuguese given name, notably borne by António Guterres, the Secretary-General of the United Nations.
  • D. Luís
    Luís is a common Portuguese male given name, historically associated with notable figures such as the poet Luís de Camões.
  • E. Lourenço
    Lourenço is a Portuguese-language surname commonly found in Lusophone countries such as Portugal, Brazil, and Angola.
  • 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: [Henrique Alvim Corrêa, hasGivenName, Henrique]
Generated description
Henrique is a masculine given name of Portuguese origin commonly used in Portuguese- and Spanish-speaking countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Henrique
Target entity description: Henrique is a masculine given name of Portuguese origin commonly used in Portuguese- and Spanish-speaking countries.
  • A. Sebastião
    Sebastião is the Portuguese variant of the given name Sebastian, commonly used in Portuguese-speaking countries.
  • B. Guilherme
    Guilherme is the Portuguese form of the given name William, commonly used in Portuguese-speaking countries.
  • C. António
    António is a common Portuguese given name, notably borne by António Guterres, the Secretary-General of the United Nations.
  • D. Luís
    Luís is a common Portuguese male given name, historically associated with notable figures such as the poet Luís de Camões.
  • E. Lourenço
    Lourenço is a Portuguese-language surname commonly found in Lusophone countries such as Portugal, Brazil, and Angola.
  • 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_69b3455175088190aa79c6e03b86647e completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35083f87c8190a3d3b323e76ab575 completed March 12, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c73d47448190a844bc13eae84a54 completed March 14, 2026, 8:38 p.m.
NEDg Description generation batch_69b5c7d04508819087b14c5c86f1e015 completed March 14, 2026, 8:40 p.m.
NED2 Entity disambiguation (via description) batch_69b5c84ccea08190a8e7e8fa93934ea2 completed March 14, 2026, 8:42 p.m.
Created at: March 12, 2026, 11:08 p.m.