Triple
T7034320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kainuu |
E163341
|
entity |
| Predicate | hasRegionalAnimal |
P30476
|
FINISHED |
| Object | bear |
—
|
LITERAL 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: bear | Statement: [Kainuu, hasRegionalAnimal, bear]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionalAnimal Context triple: [Kainuu, hasRegionalAnimal, bear]
-
A.
basedOnAnimalNativeTo
Indicates that something is derived from, inspired by, or modeled after an animal that is native to a specified geographic region.
-
B.
hasEndemicSpecies
Indicates that a place or region contains species that are native to and found only within that specific geographic area.
-
C.
hasNativeSpecies
Indicates that a particular species naturally occurs and evolved in a specified geographic area or habitat, rather than being introduced from elsewhere.
-
D.
hasWildPopulationOf
chosen
Indicates that a location or area contains a naturally occurring, non-captive population of the specified species.
-
E.
hasAnimal
Indicates that one entity possesses, keeps, or is associated with an animal.
- F. None of above.
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_69c6885d691c81908cf7d31083113886 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e458ad9c81908c3f492b317ce291 |
completed | March 27, 2026, 8:11 p.m. |
| PD | Predicate disambiguation | batch_69c6e1b9a2488190aea351d96afa5a12 |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:36 p.m.