Triple

T20828823
Position Surface form Disambiguated ID Type / Status
Subject Viazul E512772 entity
Predicate connectsCity P4245 FINISHED
Object Holguín 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: Holguín | Statement: [Viazul, connectsCity, Holguín]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Holguín
Context triple: [Viazul, connectsCity, Holguín]
  • A. Holguín chosen
    Holguín is a major city in eastern Cuba known as an important regional cultural and economic center and a gateway for tourism to nearby coastal resorts.
  • B. Holguín Province
    Holguín Province is a region in eastern Cuba known for its historic towns, sugarcane agriculture, and coastal tourism areas.
  • C. Villa Clara
    Villa Clara is a prominent Cuban baseball team known for its strong performances and rich history in the Cuban National Series.
  • D. 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.
  • E. Higüey
    Higüey is a city in the eastern Dominican Republic known as a regional commercial center and a gateway to nearby resort areas like Punta Cana.
  • 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.