Triple
T10423850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arctic fox |
E245732
|
entity |
| Predicate | preysOn |
P8767
|
FINISHED |
| Object | Arctic hares |
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 hares | Statement: [Arctic fox, preysOn, Arctic hares]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arctic hares Context triple: [Arctic fox, preysOn, Arctic hares]
-
A.
Aspen Hare
Aspen Hare is one of the official mascots of the 2002 Winter Olympics in Salt Lake City, representing speed and agility.
-
B.
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.
-
C.
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.
-
D.
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.
-
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_69d381bf3dc08190bf35a2643e4e8f22 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea2de4d48190aee65b3f6ec3cc48 |
completed | April 7, 2026, 11:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87ea554888190bf2ef31e33c0ff14 |
completed | April 10, 2026, 4:37 a.m. |
Created at: April 6, 2026, 12:12 p.m.