Triple

T2411381
Position Surface form Disambiguated ID Type / Status
Subject BOG E52196 entity
Predicate hubFor P423 FINISHED
Object LATAM Colombia E52198 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: LATAM Colombia | Statement: [BOG, hubFor, LATAM Colombia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LATAM Colombia
Context triple: [BOG, hubFor, LATAM Colombia]
  • A. LATAM Colombia chosen
    LATAM Colombia is a Colombian airline that operates domestic and international flights as part of the LATAM Airlines Group.
  • B. LATAM Brasil
    LATAM Brasil is a major Brazilian airline and subsidiary of LATAM Airlines Group, operating extensive domestic and international routes across South America and beyond.
  • C. LATAM Perú
    LATAM Perú is a major Peruvian airline and subsidiary of LATAM Airlines Group, operating domestic and international flights primarily from Lima.
  • D. LATAM Ecuador
    LATAM Ecuador is an Ecuadorian airline and regional subsidiary of LATAM Airlines Group, operating domestic and international flights primarily from its base in Guayaquil.
  • E. Colombia
    Colombia is a transcontinental country in northern South America, known for its diverse landscapes from Andes mountains to Amazon rainforest, rich cultural heritage, and major cities like Bogotá and Medellín.
  • 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_69ab495622948190bc6bc6e4cddaf645 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abc928fd608190885fcde6746a06bc completed March 7, 2026, 6:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69aeb3f00cc481909c2841a6f2ebadad completed March 9, 2026, 11:50 a.m.
Created at: March 6, 2026, 9:41 p.m.