Triple
T12333389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florida Forest Service |
E294016
|
entity |
| Predicate | typeOfForestManaged |
P30175
|
FINISHED |
| Object | state forests |
—
|
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: state forests | Statement: [Florida Forest Service, typeOfForestManaged, state forests]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfForestManaged Context triple: [Florida Forest Service, typeOfForestManaged, state forests]
-
A.
hasForestType
Indicates that an area or location is characterized by a specific type or classification of forest.
-
B.
typeOfProtectedAreasManaged
chosen
Indicates the specific categories or kinds of protected areas that an entity is responsible for managing.
-
C.
isForested
Indicates that an area or region is covered predominantly by forest or dense tree vegetation.
-
D.
forestryActivity
Indicates activities related to the management, use, or cultivation of forest resources, such as logging, planting, or forest maintenance.
-
E.
forestArea
Indicates the extent or size of land covered by forest within a given area or region.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f64ad20819080d99e57833b4b51 |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ecb5efc819086a3530282278bb1 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:53 p.m.