Triple

T20047983
Position Surface form Disambiguated ID Type / Status
Subject João Sàágua E497612 entity
Predicate givenName P17 FINISHED
Object João NE NERFINISHED

How this triple was built (2 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: João | Statement: [João Sàágua, givenName, João]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: João
Context triple: [João Sàágua, givenName, João]
  • A. João chosen
    João is a common Portuguese male given name widely used in Portuguese-speaking countries, equivalent to "John" in English.
  • B. João dos Santos
    João dos Santos is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Santos.
  • C. Sebastião
    Sebastião is the Portuguese variant of the given name Sebastian, commonly used in Portuguese-speaking countries.
  • D. Antônio
    Antônio is the given name of the Brazilian artist known professionally as Tunga, a prominent figure in contemporary sculpture and installation art.
  • E. Gonçalo
    Gonçalo is a Portuguese given name, equivalent to the Spanish name Gonzalo and commonly used for males in Portuguese-speaking countries.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da627278c88190babe4297a9df1236 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6632c085081908710cbc939ac9971 completed April 20, 2026, 5:32 p.m.
Created at: April 11, 2026, 3:37 p.m.