Triple
T7131697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Public Law 88-577 |
E166203
|
entity |
| Predicate | designatesInitialAreas |
P14731
|
FINISHED |
| Object | wilderness areas within National Forest System lands |
—
|
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: wilderness areas within National Forest System lands | Statement: [Public Law 88-577, designatesInitialAreas, wilderness areas within National Forest System lands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designatesInitialAreas Context triple: [Public Law 88-577, designatesInitialAreas, wilderness areas within National Forest System lands]
-
A.
plannedArea
Indicates that an area is designated or intended for a specific planned use or development.
-
B.
regulatesArea
Indicates that one entity exercises control or governance over the spatial extent, scope, or domain of another entity.
-
C.
territorialDesignation
chosen
Indicates that an entity is assigned, defined, or recognized in terms of a specific geographic or territorial area.
-
D.
regulatedArea
Indicates that an area is subject to specific rules, controls, or restrictions imposed by an authority.
-
E.
designedArea
Indicates that an area has been intentionally planned, shaped, or configured according to a specific design or purpose.
- 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_69c68884a9388190af42f90d1c1a7151 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e66f15b88190bc1fb0f0a8af16a6 |
completed | March 27, 2026, 8:19 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c7289881909f3b533c384f9ed4 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:44 p.m.