Triple

T13506479
Position Surface form Disambiguated ID Type / Status
Subject Alajuela Province E321025 entity
Predicate contains P35 FINISHED
Object La Fortuna E321026 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: La Fortuna | Statement: [Alajuela Province, contains, La Fortuna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Fortuna
Context triple: [Alajuela Province, contains, La Fortuna]
  • A. La Fortuna chosen
    La Fortuna is a popular Costa Rican town known as the main gateway to Arenal Volcano and its surrounding hot springs and adventure tourism.
  • B. La Fortuna
    La Fortuna is a Madrid Metro station serving the La Fortuna neighborhood in the city’s southwestern outskirts.
  • C. La Chorrera
    La Chorrera is a rapidly growing city in central Panama, known as a major suburban and commercial hub west of Panama City.
  • D. Vallehermoso
    Vallehermoso is a coastal agricultural municipality in northern Negros Oriental in the Philippines, known for its rural landscapes and proximity to the Tanon Strait.
  • E. Vallehermoso
    Vallehermoso is a rural municipality on the island of La Gomera in Spain’s Canary Islands, known for its rugged landscapes, traditional villages, and terraced agriculture.
  • 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_69d807629d6c8190998f1b9bb12d2ed0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaf8259a08190ada13c4a3078f07d completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7548e51b881909a3384812556bc3d completed May 3, 2026, 1:58 p.m.
Created at: April 9, 2026, 9:43 p.m.