Triple

T5777461
Position Surface form Disambiguated ID Type / Status
Subject Cayo Coco E127478 entity
Predicate tourismDevelopmentBegan P46376 FINISHED
Object late 20th century LITERAL 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: late 20th century | Statement: [Cayo Coco, tourismDevelopmentBegan, late 20th century]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: tourismDevelopmentBegan
Context triple: [Cayo Coco, tourismDevelopmentBegan, late 20th century]
  • A. beganDiversificationIntoTourism chosen
    Indicates that an entity started expanding its activities or operations into the tourism sector from a certain point in time.
  • B. tourismBoom
    Indicates a rapid and significant increase in tourism activity, such as visitor numbers, spending, or development, within a particular place or period.
  • C. hasTourismIndustry
    Indicates that a place or region possesses an established tourism industry, involving organized services and activities catering to visitors and travelers.
  • D. tourismImportance
    Indicates the degree to which a place or entity is significant or valuable as a destination or attraction for tourists.
  • E. hasTourismImpactOn
    Indicates that one entity affects or influences the tourism levels, patterns, or attractiveness of another entity.
  • F. None of above.

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_69c008361fa88190aefa4dc41b051e7f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02acb12c081908e4beee4a957f9f9 completed March 22, 2026, 5:45 p.m.
PD Predicate disambiguation batch_69c021d0c6088190ba670ddcdbf5ca3e completed March 22, 2026, 5:07 p.m.
Created at: March 22, 2026, 3:50 p.m.