Triple
T16128574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Almond |
E391333
|
entity |
| Predicate | sweetVarietyIsUsedFor |
P121585
|
FINISHED |
| Object | food consumption |
—
|
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: food consumption | Statement: [Almond, sweetVarietyIsUsedFor, food consumption]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sweetVarietyIsUsedFor Context triple: [Almond, sweetVarietyIsUsedFor, food consumption]
-
A.
sweetenerVariant
Indicates that one sweetening agent is a specific type, version, or alternative form of another sweetening agent.
-
B.
sweetenerType
Indicates the specific kind or category of sweetener associated with or used in relation to an entity.
-
C.
hasSugarFreeVariant
Indicates that an item has a corresponding version or option that is formulated without sugar.
-
D.
sweetenedVersionKnownAs
Indicates that one item is a sweetened form of another and is commonly referred to by a specific name.
-
E.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e20206a6f08190aa648d2bb11e7878 |
completed | April 17, 2026, 9:48 a.m. |
| PD | Predicate disambiguation | batch_69e1828518c48190a8ef3aaa46a1f639 |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e183b9d3f08190953ada68f4272996 |
completed | April 17, 2026, 12:50 a.m. |
Created at: April 10, 2026, 5:01 a.m.