Triple
T1251575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ataulfo mango |
E26886
|
entity |
| Predicate | sugarContent |
P3602
|
FINISHED |
| Object | high |
—
|
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 | Statement: [Ataulfo mango, sugarContent, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sugarContent Context triple: [Ataulfo mango, sugarContent, high]
-
A.
traditionalSweet
Indicates that something is a sweet food or dessert prepared according to long-established customs or cultural traditions.
-
B.
usesIngredient
Indicates that one entity employs or incorporates another entity as an ingredient in its composition or creation.
-
C.
hasMainIngredient
Indicates that one entity is the primary or most significant ingredient used to make another entity.
-
D.
sodiumValueApprox
Indicates that the sodium content of one entity is approximately equal to the sodium content specified or associated with another entity.
-
E.
nutritionType
chosen
Indicates the specific category or kind of nutritional characteristic or value associated with an entity.
- 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_69a49487a9c48190ba9b05348fd1b53f |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf85e1e08190ba6aac3fcd8bb3e7 |
completed | March 1, 2026, 10:36 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6c977c8190a2bf3e8b67a59beb |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.