Triple
T29287138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montes de Málaga area |
E742546
|
entity |
| Predicate | vegetationRestoration |
P70780
|
FINISHED |
| Object | reforestation with pines |
—
|
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: reforestation with pines | Statement: [Montes de Málaga area, vegetationRestoration, reforestation with pines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vegetationRestoration Context triple: [Montes de Málaga area, vegetationRestoration, reforestation with pines]
-
A.
vegetationRegrowthObserved
Indicates that the renewal or increase of plant cover has been detected following a prior disturbance or reduction.
-
B.
vegetation
Indicates that an area or object is covered with, contains, or is characterized by plant life.
-
C.
vegetationType
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
-
D.
ecosystemReconstruction
chosen
Indicates the process of restoring or recreating an ecosystem’s structure, function, and components, often after disturbance or degradation.
-
E.
landscapeManagement
Indicates the planning, implementation, and maintenance of actions that shape, conserve, or restore the physical and ecological characteristics of a landscape.
- 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_69f09121ed8c8190b4cb27be3619c262 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f6653ccf648190b65fb1141928e47e |
completed | May 2, 2026, 8:57 p.m. |
| PD | Predicate disambiguation | batch_69f660f2e3708190ab658652bcfc04d0 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 28, 2026, 12:59 p.m.