Triple

T6894049
Position Surface form Disambiguated ID Type / Status
Subject AMX E159124 entity
Predicate identifies P310 FINISHED
Object Aeroméxico E30718 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: Aeroméxico | Statement: [AMX, identifies, Aeroméxico]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aeroméxico
Context triple: [AMX, identifies, Aeroméxico]
  • A. Aeroméxico chosen
    Aeroméxico is Mexico’s flagship airline, operating domestic and international flights across the Americas, Europe, and Asia from its main hub in Mexico City.
  • B. Viva Aerobus
    Viva Aerobus is a Mexican low-cost airline known for offering budget-friendly domestic and regional flights across Mexico and select international destinations.
  • C. Copa Airlines
    Copa Airlines is the flag carrier of Panama and a major Latin American airline known for its extensive route network centered on its hub in Panama City.
  • D. LATAM Airlines Group
    LATAM Airlines Group is a major Latin American airline holding company formed by the merger of LAN Airlines and TAM Airlines, operating an extensive network of domestic and international routes across the Americas and beyond.
  • E. Avianca
    Avianca is Colombia’s flagship airline and one of Latin America’s largest carriers, operating an extensive domestic and international route network.
  • 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_69c6883568c8819081db6407e892cccc completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d931da24819096b9b205f2c0ebb0 completed March 27, 2026, 7:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7584189008190b908f530a4525885 completed March 28, 2026, 4:25 a.m.
Created at: March 27, 2026, 2:24 p.m.