Triple
T18414819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pioppi Study of Mediterranean diet |
E441858
|
entity |
| Predicate | dietCharacteristicsStudied |
P62846
|
FINISHED |
| Object | high consumption of vegetables |
—
|
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: high consumption of vegetables | Statement: [Pioppi Study of Mediterranean diet, dietCharacteristicsStudied, high consumption of vegetables]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dietCharacteristicsStudied Context triple: [Pioppi Study of Mediterranean diet, dietCharacteristicsStudied, high consumption of vegetables]
-
A.
nutritionType
Indicates the specific category or kind of nutritional characteristic or value associated with an entity.
-
B.
nutritionComponent
chosen
Indicates that one entity is a nutritional constituent, ingredient, or component of another (typically a food, diet, or nutritional product).
-
C.
nutritionStandard
Indicates that something complies with, or is evaluated against, a defined set of nutritional guidelines or requirements.
-
D.
characterizesDietAs
Indicates that one entity describes, defines, or assigns the type or nature of another entity’s diet.
-
E.
calorieProfile
Indicates the relationship between an entity and the detailed breakdown of its caloric characteristics, such as total calories and their distribution.
- 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_69d8b9eb8a508190a942fd75ebd8b1dc |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e51a26d268819098e6791dc98efcda |
completed | April 19, 2026, 6:08 p.m. |
| PD | Predicate disambiguation | batch_69e469bf7f74819096a01173493412c2 |
completed | April 19, 2026, 5:35 a.m. |
Created at: April 10, 2026, 10:47 a.m.