Triple
T18513200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bourget |
E452393
|
entity |
| Predicate | forestTypeNearby |
P41431
|
FINISHED |
| Object | Larose Forest plantation 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: Larose Forest plantation forest | Statement: [Bourget, forestTypeNearby, Larose Forest plantation forest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: forestTypeNearby Context triple: [Bourget, forestTypeNearby, Larose Forest plantation forest]
-
A.
hasNearbyForestType
chosen
Indicates that one entity is located close to, or in the vicinity of, a forest of a specified type.
-
B.
forestDistrict
Indicates that one entity functions as the forest district or forest management administrative unit responsible for the other entity.
-
C.
nearNationalForest
Indicates that one entity is located close to, but not necessarily inside, a designated national forest area.
-
D.
hasNearbyWoodland
Indicates that one entity is located close to or in the immediate vicinity of a woodland area associated with another entity.
-
E.
locatedInForest
Indicates that an entity is situated within the boundaries of a forest.
- 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_69d8d386df84819092355ebb260d848e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53348274c8190a82861b0104538e3 |
completed | April 19, 2026, 7:55 p.m. |
| PD | Predicate disambiguation | batch_69e469dbf5208190b6fc49e02a087f54 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:36 a.m.