Triple

T15369037
Position Surface form Disambiguated ID Type / Status
Subject Arctic interior of North America E367492 entity
Predicate hasWildlife P965 FINISHED
Object Arctic hare E824636 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: Arctic hare | Statement: [Arctic interior of North America, hasWildlife, Arctic hare]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arctic hare
Context triple: [Arctic interior of North America, hasWildlife, Arctic hare]
  • A. Lepus arcticus chosen
    Lepus arcticus, commonly known as the Arctic hare, is a large, white-furred hare adapted to cold Arctic environments of North America and Greenland.
  • B. Aspen Hare
    Aspen Hare is one of the official mascots of the 2002 Winter Olympics in Salt Lake City, representing speed and agility.
  • C. Arctic fox
    The Arctic fox is a small, cold-adapted mammal native to Arctic regions, known for its thick seasonal fur that changes color for camouflage in snow and tundra landscapes.
  • D. snowshoe hare
    The snowshoe hare is a North American hare species known for its large hind feet and seasonal fur color change from brown to white, which helps it move on snow and avoid predators.
  • E. Keinohrhasen
    Keinohrhasen is a popular German romantic comedy film that significantly boosted Til Schweiger’s fame as both an actor and director.
  • 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_69d85a1483788190ad93c2748e8af34b completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e4b88a881909f9575c02aed287d completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff0b50703881909ca71c985bc1c7b5 completed May 9, 2026, 10:24 a.m.
Created at: April 10, 2026, 3:18 a.m.