Triple

T7241117
Position Surface form Disambiguated ID Type / Status
Subject Isabel Allende E155356 entity
Predicate spouse P13 FINISHED
Object Miguel Frías E155356 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 Frías | Statement: [Isabel Allende, spouse, Miguel Frías]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miguel Frías
Context triple: [Isabel Allende, spouse, Miguel Frías]
  • A. Miguel Frías chosen
    Miguel Frías is a Chilean engineer best known as the former husband of renowned writer Isabel Allende.
  • B. José Antonio Núñez
    José Antonio Núñez is a Mexican football executive best known for serving as the chairman of the Dorados de Sinaloa soccer club.
  • C. Fernando Chacón
    Fernando Chacón was a Spanish naval officer best known for his role as a commander in early 18th-century Mediterranean maritime conflicts.
  • D. Fernando Medina
    Fernando Medina is a Portuguese economist and politician who served as Mayor of Lisbon and later became Portugal’s Minister of Finance.
  • E. Francisco Tomás Morales
    Francisco Tomás Morales was a Spanish royalist military officer who played a leading role in the later stages of the Venezuelan War of Independence.
  • 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_69c688143bfc81908d4176617735e601 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ea39230481908401ead83d8666cd completed March 27, 2026, 8:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8be10c5b081908210981ce9c45bd9 completed March 29, 2026, 5:52 a.m.
Created at: March 27, 2026, 2:55 p.m.