Triple

T1458414
Position Surface form Disambiguated ID Type / Status
Subject Aerolíneas Argentinas E31451 entity
Predicate callsign P1565 FINISHED
Object ARGENTINA E5383 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: ARGENTINA | Statement: [Aerolíneas Argentinas, callsign, ARGENTINA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ARGENTINA
Context triple: [Aerolíneas Argentinas, callsign, ARGENTINA]
  • A. Argentina chosen
    Argentina is a large South American nation known for its diverse landscapes from the Andes to the Pampas, its vibrant culture including tango and football, and its capital city Buenos Aires.
  • B. Uruguay
    Uruguay is a small South American country known for its stable democracy, high standard of living, and Atlantic coastline between Brazil and Argentina.
  • C. Paraguay
    Paraguay is a landlocked country in central South America known for its bilingual Spanish and Guaraní culture and its location along the Paraguay and Paraná rivers.
  • D. Chile
    Chile is a long, narrow South American country stretching along the Pacific coast, renowned for its diverse climates, stable economy, and world-class astronomical observatories.
  • E. southern Argentina
    Southern Argentina is a sparsely populated region of Argentina characterized by its Patagonian landscapes, cold climate, and diverse wildlife.
  • 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_69a49917dfc081909acdbdf5d684f1ef completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c59a462881908e84b27846a6bc04 completed March 1, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69ada962149881908c6ecba8347e22d7 completed March 8, 2026, 4:52 p.m.
Created at: March 1, 2026, 8 p.m.