Triple

T18322219
Position Surface form Disambiguated ID Type / Status
Subject Zoo Atlanta E438910 entity
Predicate hasExhibit P35 FINISHED
Object Asian Forest NE NERFINISHED

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: Asian Forest | Statement: [Zoo Atlanta, hasExhibit, Asian Forest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Asian Forest
Context triple: [Zoo Atlanta, hasExhibit, Asian Forest]
  • A. Asian Forest Sanctuary chosen
    Asian Forest Sanctuary is a themed zoo exhibit that recreates Asian forest habitats to showcase and conserve species such as tigers, elephants, and other wildlife from the region.
  • B. Japan Forest
    Japan Forest is a themed exhibit area at Osaka’s Aquarium Kaiyukan that recreates a lush Japanese woodland ecosystem with native plants and animals.
  • C. Southeast Asian rainforests
    Southeast Asian rainforests are vast, biodiverse tropical forests known for their rich ecosystems, high rainfall, and critical role in global climate regulation.
  • D. Karura Forest
    Karura Forest is a protected urban forest in Nairobi, Kenya, known for its walking trails, waterfalls, caves, and rich biodiversity.
  • E. Forêt d’Orient
    Forêt d’Orient is a large forested area in northeastern France known for its lakes, wetlands, and rich biodiversity within the Champagne region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b916a2d081909e249e4902f6aad9 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e50aa7be288190983f13e9c7061b6d completed April 19, 2026, 5:02 p.m.
Created at: April 10, 2026, 10:36 a.m.