Triple

T11064532
Position Surface form Disambiguated ID Type / Status
Subject Marcos Maceo E261590 entity
Predicate givenName P17 FINISHED
Object Marcos E352679 NE FINISHED

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: Marcos | Statement: [Marcos Maceo, givenName, Marcos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marcos
Context triple: [Marcos Maceo, givenName, Marcos]
  • A. Marcos chosen
    Marcos is a masculine given name, commonly used in Spanish- and Portuguese-speaking countries, that derives from the Latin name Marcus.
  • B. Teodoro
    Teodoro is a given name, commonly used in Romance-language countries, that corresponds to the English name Theodore.
  • C. Juan Vicente
    Juan Vicente is a Venezuelan military leader and politician of the early 19th century, best known as the father of independence hero Simón Bolívar.
  • D. Augusto Vargas Alzamora
    Augusto Vargas Alzamora was a Peruvian Cardinal of the Roman Catholic Church who served as Archbishop of Lima and was known for his outspoken defense of human rights and democracy.
  • E. Mariano
    Mariano is a masculine given name of Spanish and Portuguese origin, commonly used in various Spanish-speaking and Latin cultures.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6aa98650481908609c7c56bfa7902 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d798edcab881909da1ba0394020ef8 completed April 9, 2026, 12:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3c8977f98819082dec025e92782da completed April 18, 2026, 6:08 p.m.
Created at: April 8, 2026, 9:26 p.m.