Triple
T20144812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tillamook Burn |
E491274
|
entity |
| Predicate | reforestationMethod |
P99050
|
FINISHED |
| Object | hand planting of seedlings |
—
|
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: hand planting of seedlings | Statement: [Tillamook Burn, reforestationMethod, hand planting of seedlings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reforestationMethod Context triple: [Tillamook Burn, reforestationMethod, hand planting of seedlings]
-
A.
forestryActivity
Indicates activities related to the management, use, or cultivation of forest resources, such as logging, planting, or forest maintenance.
-
B.
treePlanting
chosen
Indicates the action of placing and establishing a tree in the ground at a chosen location.
-
C.
treeUse
Indicates the way in which a tree is utilized or purposed within a given context.
-
D.
isForested
Indicates that an area or region is covered predominantly by forest or dense tree vegetation.
-
E.
reconstructionMethod
Indicates the technique or process used to reconstruct, restore, or rebuild something from its original or fragmented state.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6679d89688190ae88d81002d16d6e |
completed | April 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69e54cfb0d0081908e789b9b57e96668 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:33 p.m.