Triple

T1542987
Position Surface form Disambiguated ID Type / Status
Subject National Zoo E32911 entity
Predicate hasAnimal P13551 FINISHED
Object komodo dragon E124635 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: komodo dragon | Statement: [National Zoo, hasAnimal, komodo dragon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: komodo dragon
Context triple: [National Zoo, hasAnimal, komodo dragon]
  • A. Komodo dragon chosen
    The Komodo dragon is the world’s largest living lizard, a powerful carnivorous reptile native to a few Indonesian islands.
  • B. Komodo
    Komodo is an Indonesian island best known as the natural habitat of the Komodo dragon and a key part of Komodo National Park.
  • C. Burmese python
    The Burmese python is a large, nonvenomous constrictor snake native to Southeast Asia that has become a highly destructive invasive species in the Florida Everglades.
  • D. Lagarto
    Lagarto is a municipality in the Brazilian state of Sergipe, known for its agricultural activities and growing regional commerce.
  • E. Nile crocodile
    The Nile crocodile is a large and aggressive African crocodilian known for inhabiting rivers, lakes, and wetlands and being one of the continent’s most formidable predators.
  • 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_69a885ed29088190a3c2d5a3d100c16e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9084140f0819098c81d295d08d480 completed March 5, 2026, 4:36 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad309baebc81908240a0370bad9935 completed March 8, 2026, 8:17 a.m.
Created at: March 4, 2026, 7:26 p.m.