Triple

T20828842
Position Surface form Disambiguated ID Type / Status
Subject Viazul E512772 entity
Predicate notableRoute P22 FINISHED
Object Havana–Varadero NE NERFINISHED

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: Havana–Varadero | Statement: [Viazul, notableRoute, Havana–Varadero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Havana–Varadero
Context triple: [Viazul, notableRoute, Havana–Varadero]
  • A. Varadero chosen
    Varadero is a major Cuban beach resort town on the Hicacos Peninsula, renowned for its long white-sand beaches and tourism infrastructure.
  • B. Las Villas
    Las Villas was a historic central province of Cuba that served as a significant theater of military operations during the Cuban War of Independence.
  • C. Cienfuegos
    Cienfuegos is a coastal city in central Cuba known for its French-influenced architecture and historic bay.
  • D. Pinar del Río
    Pinar del Río is a city in western Cuba known for its tobacco production and as a gateway to the Viñales Valley.
  • E. Pinar del Río, Cuba
    Pinar del Río, Cuba is a western Cuban city and provincial capital known for its rich tobacco-growing region and traditional cigar production.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4ce39108190a6e8e5df4f1c8dc5 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c32030c081908249449aae5925c8 completed April 21, 2026, 12:21 a.m.
Created at: April 16, 2026, 12:42 p.m.