Triple
T12367165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atlantic white cedar forest |
E294901
|
entity |
| Predicate | hasNutrientStatus |
P104805
|
FINISHED |
| Object | nutrient-poor |
—
|
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: nutrient-poor | Statement: [Atlantic white cedar forest, hasNutrientStatus, nutrient-poor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNutrientStatus Context triple: [Atlantic white cedar forest, hasNutrientStatus, nutrient-poor]
-
A.
nutritionComponent
Indicates that one entity is a nutritional constituent, ingredient, or component of another (typically a food, diet, or nutritional product).
-
B.
nutritionStandard
Indicates that something complies with, or is evaluated against, a defined set of nutritional guidelines or requirements.
-
C.
nutritionType
Indicates the specific category or kind of nutritional characteristic or value associated with an entity.
-
D.
hasCalories
Indicates that an entity contains a specified amount of caloric energy.
-
E.
hasPrimaryCarbohydrate
Indicates that one entity has another entity as its main or principal carbohydrate component.
- F. None of above. chosen
Provenance (4 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d942a2d6e08190a13c7ff89af09354 |
completed | April 10, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69d93ecf6b548190a394b6b56a0c1c68 |
completed | April 10, 2026, 6:17 p.m. |
| PDg | Predicate description generation | batch_69d9429ff2bc8190b09adf8f57fad451 |
completed | April 10, 2026, 6:34 p.m. |
Created at: April 8, 2026, 9:54 p.m.