Triple

T17540833
Position Surface form Disambiguated ID Type / Status
Subject Miguel Ángel Asturias E427193 entity
Predicate givenName P17 FINISHED
Object Miguel 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: Miguel | Statement: [Miguel Ángel Asturias, givenName, Miguel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miguel
Context triple: [Miguel Ángel Asturias, givenName, Miguel]
  • A. 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.
  • B. Miguel
    Miguel is an American R&B singer, songwriter, and producer known for his smooth vocals and genre-blending, atmospheric sound.
  • C. Maixabel
    Maixabel is a Spanish drama film that portrays the true story of Maixabel Lasa, a woman who confronts the ETA terrorists who murdered her husband, exploring themes of grief, forgiveness, and reconciliation.
  • D. Niño
    Niño is a Spanish surname commonly borne by individuals and families in Spanish-speaking countries.
  • E. 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.
  • 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_69d889df6dc081908f67dbadc03c07ee completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e4545e64448190a2a63bc13f549027 completed April 19, 2026, 4:04 a.m.
Created at: April 10, 2026, 5:49 a.m.