Triple

T11316265
Position Surface form Disambiguated ID Type / Status
Subject Luís de Ataíde E267975 entity
Predicate givenName P17 FINISHED
Object Luís E100712 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: Luís | Statement: [Luís de Ataíde, givenName, Luís]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luís
Context triple: [Luís de Ataíde, givenName, Luís]
  • A. Luís chosen
    Luís is a common Portuguese male given name, historically associated with notable figures such as the poet Luís de Camões.
  • B. Fernando
    "Fernando" is a popular 1976 ballad by Swedish pop group ABBA, known for its nostalgic, storytelling lyrics and melodic harmonies.
  • C. Fernando
    Fernando is a masculine given name of Spanish and Portuguese origin, commonly used in many Spanish-speaking and Lusophone countries.
  • D. Fernando
    Fernando was the given name of the Duke of Alba who served as governor-general, a prominent Spanish noble and military leader.
  • E. Fernando
    Fernando is the given name of Fernando Primo de Rivera, a 19th-century Spanish general and politician who briefly served as Prime Minister of Spain.
  • 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_69d6aaca5c24819083db46a30d86cb34 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9c3cf748190987838029d9f7fff completed April 9, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69e525c35538819085d76f7cdf362316 completed April 19, 2026, 6:58 p.m.
Created at: April 8, 2026, 9:32 p.m.