Triple

T199561
Position Surface form Disambiguated ID Type / Status
Subject Panamanian golden frog E4071 entity
Predicate endemicTo P954 FINISHED
Object Panama E1142 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: Panama | Statement: [Panamanian golden frog, endemicTo, Panama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Panama
Context triple: [Panamanian golden frog, endemicTo, Panama]
  • A. Panama chosen
    Panama is a Central American country known for the Panama Canal, a major international shipping route connecting the Atlantic and Pacific Oceans.
  • B. Costa Rica
    Costa Rica is a Central American country renowned for its political stability, rich biodiversity, and strong environmental conservation efforts.
  • C. Nicaragua
    Nicaragua is a Central American country known for its volcanic landscapes, large lakes, and colonial-era architecture.
  • D. Ecuador
    Ecuador is a South American country on the Pacific coast, known for its diverse geography that includes part of the Amazon rainforest, the Andean highlands, and the Galápagos Islands.
  • E. Colombia
    Colombia is a transcontinental country in northern South America, known for its diverse landscapes from Andes mountains to Amazon rainforest, rich cultural heritage, and major cities like Bogotá and Medellín.
  • 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_69a254bca59881909a15e1496f1508c7 completed Feb. 28, 2026, 2:36 a.m.
NER Named-entity recognition batch_69a25bcc6dc88190b8c24b485588dfe4 completed Feb. 28, 2026, 3:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3dd28b4008190bce7ea85b1c9988e completed March 1, 2026, 6:31 a.m.
Created at: Feb. 28, 2026, 2:44 a.m.