Triple
T17076544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sprite Lymonade |
E414361
|
entity |
| Predicate | primaryIngredientCategory |
P40800
|
FINISHED |
| Object | carbonated water |
—
|
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: carbonated water | Statement: [Sprite Lymonade, primaryIngredientCategory, carbonated water]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryIngredientCategory Context triple: [Sprite Lymonade, primaryIngredientCategory, carbonated water]
-
A.
primaryFoodType
Indicates the main category of food that characterizes what an entity primarily eats or serves.
-
B.
ingredientType
chosen
Indicates that one entity is classified as a specific type or category of ingredient in relation to another.
-
C.
primaryFood
Indicates that one entity serves as the main or most important food source for another entity.
-
D.
hasMainIngredient
Indicates that one entity is the primary or most significant ingredient used to make another entity.
-
E.
primaryFlavor
Indicates the dominant or most characteristic taste associated with an item relative to other possible flavors.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbc559388190b685504cca6ed62b |
completed | April 18, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69e35d642f74819098c014135e249b27 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:34 a.m.