Triple

T5350630
Position Surface form Disambiguated ID Type / Status
Subject Toronto Zoo E124168 entity
Predicate hasSection P35 FINISHED
Object Americas E17691 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: Americas | Statement: [Toronto Zoo, hasSection, Americas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Americas
Context triple: [Toronto Zoo, hasSection, Americas]
  • A. Americas chosen
    The Americas are the combined landmasses of North and South America, encompassing a vast region of diverse cultures, climates, and ecosystems in the Western Hemisphere.
  • B. North America
    North America is a large continent in the Northern and Western Hemispheres that includes countries such as the United States, Canada, and Mexico.
  • C. América
    América is a popular Mexican professional football club based in Mexico City, widely recognized as one of the most successful and supported teams in Liga MX.
  • D. Amerika
    Amerika is a novel by Franz Kafka that follows a young European immigrant’s surreal and often absurd experiences in the United States.
  • E. Latin America
    Latin America is a culturally diverse region of the Americas, spanning Mexico, Central and South America, and much of the Caribbean, where Romance languages—primarily Spanish and Portuguese—predominate.
  • 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_69bd464be27081908807b40b75c1bbae completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd860fe4048190846a933d0e1b9386 completed March 20, 2026, 5:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf33395b248190a1552288a3d5213c completed March 22, 2026, 12:09 a.m.
Created at: March 20, 2026, 2:01 p.m.