Triple
T1193533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fontainebleau |
E25615
|
entity |
| Predicate | forestStatus |
P18514
|
FINISHED |
| Object | protected forest |
—
|
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: protected forest | Statement: [Fontainebleau, forestStatus, protected forest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: forestStatus Context triple: [Fontainebleau, forestStatus, protected forest]
-
A.
hasNationalForest
Indicates that a place or jurisdiction contains, includes, or is home to at least one designated national forest.
-
B.
ecologicalStatus
chosen
Indicates the condition or health of an ecosystem or environment, often in terms of its quality, integrity, or degree of disturbance.
-
C.
hasMajorForest
Indicates that an entity possesses or contains a large, significant forested area.
-
D.
hasFireRegime
Indicates that an area or ecosystem is characterized by a particular pattern, frequency, and intensity of fires over time.
-
E.
vegetationType
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
- 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_69a49429f5ec8190a6a205eb0ae81e5e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd7743548190a70d3f3c7378aaa7 |
completed | March 1, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5bacc481909e8dfd5215e4711a |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.