Triple
T10243542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Payette National Forest |
E243658
|
entity |
| Predicate | hasRuggedWilderness |
P39516
|
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, hasRuggedWilderness, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRuggedWilderness Context triple: [Payette National Forest, hasRuggedWilderness, true]
-
A.
hasWildernessArea
Indicates that one entity possesses, contains, or is associated with a designated wilderness area.
-
B.
hasRugged
chosen
Indicates that something possesses a rough, uneven, or tough physical character or surface.
-
C.
containsWildernessArea
Indicates that one entity geographically includes or encompasses a designated wilderness area within its boundaries.
-
D.
hasWildernessCharacter
Indicates that an area possesses qualities or attributes associated with being wild, natural, and largely unaffected by human development or control.
-
E.
hasRockyTerrain
Indicates that the subject possesses or is characterized by rough, uneven, or rock-covered ground or surface conditions.
- 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.