Triple
T1251564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ataulfo mango |
E26886
|
entity |
| Predicate | culinaryUse |
P25824
|
FINISHED |
| Object | fresh eating |
—
|
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: fresh eating | Statement: [Ataulfo mango, culinaryUse, fresh eating]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: culinaryUse Context triple: [Ataulfo mango, culinaryUse, fresh eating]
-
A.
usesIngredient
Indicates that one entity employs or incorporates another entity as an ingredient in its composition or creation.
-
B.
cuisine
Indicates the type or style of food traditionally associated with or served by an entity (such as a restaurant or region).
-
C.
usesCookingMethod
Indicates that one entity prepares or processes another entity by applying a specific cooking technique or method.
-
D.
cuisineFeature
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
-
E.
traditionalUse
Indicates that something is used or practiced according to long-established customs, habits, or cultural traditions.
- 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_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. |
| PDg | Predicate description generation | batch_69a4bc49693c8190978ec63a5171d342 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:47 p.m.