Triple
T10243543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Payette National Forest |
E243658
|
entity |
| Predicate | hasExtensiveConiferForests |
P57219
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Payette National Forest, hasExtensiveConiferForests, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExtensiveConiferForests Context triple: [Payette National Forest, hasExtensiveConiferForests, true]
-
A.
isConifer
Indicates that the subject is a coniferous plant, typically bearing cones and having needle-like or scale-like evergreen leaves.
-
B.
hasForestType
chosen
Indicates that an area or location is characterized by a specific type or classification of forest.
-
C.
hasMajorForest
Indicates that an entity possesses or contains a large, significant forested area.
-
D.
isForested
Indicates that an area or region is covered predominantly by forest or dense tree vegetation.
-
E.
hasNationalForest
Indicates that a place or jurisdiction contains, includes, or is home to at least one designated national forest.
- 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d328272c8190a3548d7f7f38cfc4 |
completed | April 7, 2026, 9:49 a.m. |
| PD | Predicate disambiguation | batch_69d4d1ebd6c88190a1f3f4a72a99d6fe |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:25 a.m.