Triple

T428580
Position Surface form Disambiguated ID Type / Status
Subject 1936 Summer Olympics E9663 entity
Predicate hostCityBidRivals P10422 FINISHED
Object Buenos Aires 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 | Statement: [1936 Summer Olympics, hostCityBidRivals, Buenos Aires]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Buenos Aires
Context triple: [1936 Summer Olympics, hostCityBidRivals, Buenos Aires]
  • 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. Colonia Buenos Aires
    Colonia Buenos Aires is a neighborhood located within the Cuauhtémoc borough in central Mexico City.
  • C. Montevideo
    Montevideo is the capital and largest city of Uruguay, serving as the country’s main political, economic, and cultural center.
  • D. Comodoro Rivadavia
    Comodoro Rivadavia is a coastal city in southern Argentina known as a key oil industry hub and one of the main urban centers of Patagonia.
  • E. La Boca
    La Boca is a colorful, working-class neighborhood in Buenos Aires famous for its vividly painted houses, tango culture, and the Boca Juniors football stadium.
  • 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_69a2e801e1d48190b505d1dd336b52ac completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2f01be4108190b4c13346afd95a03 completed Feb. 28, 2026, 1:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69a447fa97ac8190b8a19ded2d0f520e completed March 1, 2026, 2:06 p.m.
Created at: Feb. 28, 2026, 1:11 p.m.