Triple

T22471291
Position Surface form Disambiguated ID Type / Status
Subject Salobreña E555507 entity
Predicate locatedOn P40 FINISHED
Object Costa Tropical 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: Costa Tropical | Statement: [Salobreña, locatedOn, Costa Tropical]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Costa Tropical
Context triple: [Salobreña, locatedOn, Costa Tropical]
  • A. Costa Tropical chosen
    Costa Tropical is a coastal region in the province of Granada in southern Spain, known for its subtropical climate, beaches, and agricultural production of tropical fruits.
  • B. La Costeña
    La Costeña is a Nicaraguan regional airline that operates domestic flights connecting Managua with various destinations across the country.
  • C. Camaya Coast
    Camaya Coast is a popular beach and resort development in Mariveles, Bataan, known for its white-sand shoreline, recreational amenities, and residential and tourism facilities.
  • D. Costa Chica
    Costa Chica is a coastal region in southern Mexico known for its Afro-Mexican communities, rich cultural traditions, and Pacific shoreline spanning parts of Oaxaca and Guerrero.
  • E. Costa Grande
    Costa Grande is a coastal region in the Mexican state of Guerrero known for its beaches, fishing communities, and agricultural 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_69e11e52c2048190952dc5df209b9bed completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15bdf6dfc8190aa8dc80ad92a9267 completed April 29, 2026, 1:16 a.m.
Created at: April 16, 2026, 8:48 p.m.