Triple
T12033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sierra Nevada |
E245
|
entity |
| Predicate | ecoregion |
P948
|
FINISHED |
| Object | Sierra Nevada forests |
—
|
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: Sierra Nevada forests | Statement: [Sierra Nevada, ecoregion, Sierra Nevada forests]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ecoregion Context triple: [Sierra Nevada, ecoregion, Sierra Nevada forests]
-
A.
basinCountry
Indicates the country or countries within whose territory a river basin or drainage area is primarily located or through which it significantly extends.
-
B.
continent
Indicates that one entity is a continent on which the other entity is geographically located or to which it belongs.
-
C.
areaWater
Indicates the relationship between a geographic entity and the total area of its surface that is covered by water.
-
D.
sourceRegion
Indicates the geographic or spatial region from which something originates or is derived.
-
E.
hasCoastlineOn
Indicates that one entity’s coastline borders or is directly adjacent to a specified body of water.
- F. None of above. chosen
Provenance (4 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a241ea1ea081908e8a81ca97531ba5 |
completed | Feb. 28, 2026, 1:16 a.m. |
| PD | Predicate disambiguation | batch_69a23fe7da8c8190aea795b62cb91621 |
completed | Feb. 28, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69a241e933288190b02ef5369f7b8834 |
completed | Feb. 28, 2026, 1:16 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.