Triple

T8167259
Position Surface form Disambiguated ID Type / Status
Subject Carlos Menem E190722 entity
Predicate deathPlace P21 FINISHED
Object Buenos Aires, Argentina E5323 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: Buenos Aires, Argentina | Statement: [Carlos Menem, deathPlace, Buenos Aires, Argentina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Buenos Aires, Argentina
Context triple: [Carlos Menem, deathPlace, Buenos Aires, Argentina]
  • A. Buenos Aires chosen
    Buenos Aires is the capital and largest city of Argentina, known for its rich European-influenced culture, tango music and dance, and vibrant urban life.
  • B. Mar del Plata
    Mar del Plata is a major Argentine Atlantic coastal city renowned as a popular beach resort and tourist destination.
  • C. Santa Fe, Argentina
    Santa Fe, Argentina is a major river port city and the capital of Santa Fe Province, located in northeastern Argentina along the Paraná and Salado rivers.
  • D. Colonia Buenos Aires
    Colonia Buenos Aires is a neighborhood located within the Cuauhtémoc borough in central Mexico City.
  • E. Colón, Argentina
    Colón, Argentina is a riverside city in Entre Ríos Province known for its beaches on the Uruguay River, hot springs, and role as a popular tourist gateway to nearby natural attractions.
  • 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_69ca82c0ef14819083713f4473dd847c completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb46698fb88190a6d520b05cb9b03e completed March 31, 2026, 3:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfab01c58c81909148dacad2dc7667 completed April 3, 2026, 11:56 a.m.
Created at: March 30, 2026, 5:39 p.m.