Triple

T6685687
Position Surface form Disambiguated ID Type / Status
Subject Luis Figo E152093 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: [Luis Figo, givenName, Luís]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luís
Context triple: [Luis Figo, 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 the given name of Fernando Primo de Rivera, a 19th-century Spanish general and politician who briefly served as Prime Minister of Spain.
  • D. Fernando
    Fernando is a masculine given name of Spanish and Portuguese origin, commonly used in many Spanish-speaking and Lusophone countries.
  • E. Fernando
    Fernando is the given name of Salgueiro Maia, a key Portuguese military officer who played a leading role in the Carnation Revolution.
  • 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_69c687f9977c819097e7f5ada4fe522e completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b12483948190ba426076919edc48 completed March 27, 2026, 4:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69c72f7df860819099d50871dbe08ad9 completed March 28, 2026, 1:31 a.m.
Created at: March 27, 2026, 2:04 p.m.