Triple
T45437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alaska |
E890
|
entity |
| Predicate | hasWildlife |
P965
|
FINISHED |
| Object | brown bears |
—
|
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: brown bears | Statement: [Alaska, hasWildlife, brown bears]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWildlife Context triple: [Alaska, hasWildlife, brown bears]
-
A.
hasEndemicSpecies
Indicates that a place or region contains species that are native to and found only within that specific geographic area.
-
B.
fauna
Indicates that an entity is an animal or part of the animal life associated with a particular place or context.
-
C.
notableSpecies
chosen
Indicates that the subject is known for, or significantly associated with, the specified species.
-
D.
hasBiosphere
Indicates that an entity possesses or supports a biosphere, i.e., a region where living organisms and ecological processes exist.
-
E.
hasNaturalFeature
Indicates that one entity possesses, contains, or is characterized by a particular natural feature (such as a mountain, river, forest, or coastline).
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24ba7016481909d595402712db6e2 |
completed | Feb. 28, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69a24abbd32c81908cec461d9097662e |
completed | Feb. 28, 2026, 1:54 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.