Triple

T784783
Position Surface form Disambiguated ID Type / Status
Subject Costa Rica E16577 entity
Predicate capital P234 FINISHED
Object San José E29798 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: San José | Statement: [Costa Rica, capital, San José]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: San José
Context triple: [Costa Rica, capital, San José]
  • A. San José chosen
    San José is the capital and largest city of Costa Rica, known for its political, economic, and cultural significance in Central America.
  • B. San Jose
    San Jose is a major technology and innovation hub in Silicon Valley and one of the largest cities in Northern California.
  • C. San Fernando
    San Fernando is a Philippine city on the island of Luzon known as a regional commercial and administrative center.
  • D. San Fernando
    San Fernando is a major industrial and commercial city located in the southern part of Trinidad, known for its energy sector and bustling urban center.
  • E. San Fernando
    San Fernando is a principal urban center and agricultural hub in central Chile’s O’Higgins Region.
  • 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_69a4936ad1fc81908f190208059ccf78 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a769dc6481908f12e872f997acf3 completed March 1, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69acddf440848190aa5019ffcedd4859 completed March 8, 2026, 2:24 a.m.
Created at: March 1, 2026, 7:37 p.m.