Triple

T121036
Position Surface form Disambiguated ID Type / Status
Subject Ministerial Conference E2443 entity
Predicate meetsIn P40 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: [Ministerial Conference, meetsIn, Buenos Aires]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Buenos Aires
Context triple: [Ministerial Conference, meetsIn, 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. 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.
  • C. Bariloche
    Bariloche is a popular Argentine city in the Andean region known for its lakes, mountains, skiing, and Swiss-style alpine architecture.
  • D. Santiago
    Santiago is the capital and primary economic, political, and cultural center of Chile, located in the country’s central valley.
  • E. Santiago
    Santiago was one of the smaller support vessels in Ferdinand Magellan’s early 16th-century expedition to circumnavigate the globe, primarily used for scouting and exploration along the South American coast.
  • 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_69a2506c5428819085c28a8884790e29 completed Feb. 28, 2026, 2:18 a.m.
NER Named-entity recognition batch_69a25739ef28819093f3f0e6bb670201 completed Feb. 28, 2026, 2:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69a31619063c8190879a726867d4b46d completed Feb. 28, 2026, 4:21 p.m.
Created at: Feb. 28, 2026, 2:24 a.m.