Triple
T2595875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | south-central France |
E58228
|
entity |
| Predicate | notableProtectedAreas |
P30175
|
FINISHED |
| Object | regional natural parks |
—
|
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: regional natural parks | Statement: [south-central France, notableProtectedAreas, regional natural parks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableProtectedAreas Context triple: [south-central France, notableProtectedAreas, regional natural parks]
-
A.
hasNationalScenicArea
Indicates that an entity is designated as or associated with a National Scenic Area.
-
B.
nationalPark
Indicates that a location is designated and managed as a national park by a governing authority.
-
C.
typeOfProtectedAreasManaged
chosen
Indicates the specific categories or kinds of protected areas that an entity is responsible for managing.
-
D.
managesProtectedArea
Indicates that an entity has responsibility for overseeing, administering, and caring for a designated protected area.
-
E.
marineProtectedAreaOf
Indicates that one entity is designated as a marine protected area that encompasses, is associated with, or provides protection for the other entity.
- 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_69ab4ac14040819098b13f4a27d5c8ff |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd42978f881909f217e7ec9ac3144 |
completed | March 7, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69abd0d344988190a18dd93b13e002e6 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:49 p.m.