Triple
T16873375
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tustumena Lake |
E421230
|
entity |
| Predicate | hasVegetationNearby |
P33602
|
FINISHED |
| Object | boreal 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: boreal forest | Statement: [Tustumena Lake, hasVegetationNearby, boreal forest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVegetationNearby Context triple: [Tustumena Lake, hasVegetationNearby, boreal forest]
-
A.
hasVegetationIssue
Indicates that an entity is affected by a problem, damage, or abnormal condition related to its vegetation or plant life.
-
B.
hasNearbyWoodland
Indicates that one entity is located close to or in the immediate vicinity of a woodland area associated with another entity.
-
C.
hasNearbyGreenSpace
chosen
Indicates that an entity is located close to an area of green space, such as a park, garden, or natural vegetation.
-
D.
hasAttractiveFoliage
Indicates that an entity possesses foliage that is visually appealing or ornamental in appearance.
-
E.
vegetation
Indicates that an area or object is covered with, contains, or is characterized by plant life.
- 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_69d889d470fc8190b4aec199636c0c56 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3b7f40410819088db22fa0d1eb808 |
completed | April 18, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69e32b90ec3c819099c51bb7baf2984c |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:29 a.m.