Triple
T15719111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sihlwald |
E381042
|
entity |
| Predicate | forestManagement |
P41063
|
FINISHED |
| Object | near-natural forest management |
—
|
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: near-natural forest management | Statement: [Sihlwald, forestManagement, near-natural forest management]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: forestManagement Context triple: [Sihlwald, forestManagement, near-natural forest management]
-
A.
forestryActivity
chosen
Indicates activities related to the management, use, or cultivation of forest resources, such as logging, planting, or forest maintenance.
-
B.
forestDistrict
Indicates that one entity functions as the forest district or forest management administrative unit responsible for the other entity.
-
C.
landscapeManagement
Indicates the planning, implementation, and maintenance of actions that shape, conserve, or restore the physical and ecological characteristics of a landscape.
-
D.
forestArea
Indicates the extent or size of land covered by forest within a given area or region.
-
E.
forestCoverCharacteristic
Indicates a relationship where a forested area possesses a specific attribute or quality related to its tree or vegetation cover.
- 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f932a248190b65ecfb2bc56e715 |
completed | April 16, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69e00526759c819088b80d85138b8974 |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:45 a.m.