Triple

T9708498
Position Surface form Disambiguated ID Type / Status
Subject Miguel Lerdo de Tejada E234959 entity
Predicate givenName P17 FINISHED
Object Miguel E95446 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: Miguel | Statement: [Miguel Lerdo de Tejada, givenName, Miguel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miguel
Context triple: [Miguel Lerdo de Tejada, givenName, Miguel]
  • A. Miguel
    Miguel is an American R&B singer, songwriter, and producer known for his smooth vocals and genre-blending, atmospheric sound.
  • B. Miguel chosen
    Miguel is a Spanish given name widely used in the Hispanic world, notably borne by figures such as Mexican independence leader Miguel Hidalgo y Costilla.
  • C. Rodrigo
    Rodrigo is a masculine given name of Spanish and Portuguese origin, derived from the Germanic name Roderick and commonly used across the Spanish-speaking world.
  • D. Luis
    Luis is a comedic supporting character in the Marvel Cinematic Universe, best known as Scott Lang’s fast-talking friend and former cellmate in the Ant-Man films.
  • E. Luis
    Luis is the Spanish given name of Louis I of Spain, an 18th-century Bourbon king who briefly ruled the country.
  • 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_69ca84cc78808190a56f3402b7c139a7 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9da5e09081909456909d768611e6 completed April 1, 2026, 10:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69d19f8476e08190865700679069dee6 completed April 4, 2026, 11:32 p.m.
Created at: March 30, 2026, 8:19 p.m.