Triple

T1196249
Position Surface form Disambiguated ID Type / Status
Subject AeroCaribbean E25673 entity
Predicate servedCity P3936 FINISHED
Object Holguín E60150 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: Holguín | Statement: [AeroCaribbean, servedCity, Holguín]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Holguín
Context triple: [AeroCaribbean, servedCity, Holguín]
  • A. Holguín Province
    Holguín Province is a region in eastern Cuba known for its historic towns, sugarcane agriculture, and coastal tourism areas.
  • B. Villa Clara
    Villa Clara is a prominent Cuban baseball team known for its strong performances and rich history in the Cuban National Series.
  • C. Camagüey
    Camagüey is one of Cuba’s largest and oldest cities, known for its colonial architecture, maze-like historic center, and status as a key cultural and economic hub in the country’s interior.
  • D. Holguín, Cuba chosen
    Holguín, Cuba is a major city in eastern Cuba known for its historic plazas, nearby beaches, and role as an important cultural and economic center in the region.
  • E. Cienfuegos
    Cienfuegos is a coastal city in central Cuba known for its French-influenced architecture and historic bay.
  • 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_69a49429f5ec8190a6a205eb0ae81e5e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd7a756c819085d695acfffeaceb completed March 1, 2026, 10:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69ada0b77f008190893627daee29c441 completed March 8, 2026, 4:15 p.m.
Created at: March 1, 2026, 7:46 p.m.