Triple
T30844529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helianthus tuberosus |
E785598
|
entity |
| Predicate | tuberCarbohydrate |
P102682
|
FINISHED |
| Object | inulin |
—
|
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: inulin | Statement: [Helianthus tuberosus, tuberCarbohydrate, inulin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tuberCarbohydrate Context triple: [Helianthus tuberosus, tuberCarbohydrate, inulin]
-
A.
hasPrimaryCarbohydrate
chosen
Indicates that one entity has another entity as its main or principal carbohydrate component.
-
B.
sugarContentCategory
Indicates the classification of something based on how much sugar it contains (e.g., low, medium, or high sugar content).
-
C.
carbohydratesPer12Ounces
Indicates the amount of carbohydrates contained in a 12-ounce serving of a given item.
-
D.
hasSugarContent
Indicates that one entity possesses or contains a specified amount or level of sugar.
-
E.
calorieLevel
Indicates the relationship between an entity and the amount of calories it contains or provides, typically categorized by intensity or range (e.g., low, medium, high).
- 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_69f224b850848190a4af4ccf8ddadcdf |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69145041c81909275df4e885f090a |
completed | May 3, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69f68b7d2794819092fef8a63f4f3de8 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 8:46 p.m.