Triple
T7426241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Bull Sugarfree |
E171374
|
entity |
| Predicate | containsPhenylalanine |
P23191
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Red Bull Sugarfree, containsPhenylalanine, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsPhenylalanine Context triple: [Red Bull Sugarfree, containsPhenylalanine, yes]
-
A.
containsAllergenicCompound
chosen
Indicates that the subject entity includes one or more compounds known to cause allergic reactions.
-
B.
containsAdditives
Indicates that one entity includes or is composed of additional substances or ingredients beyond its primary or original components.
-
C.
proteinContent
Indicates the amount or proportion of protein present in a given entity or substance.
-
D.
hasProteinFeature
Indicates that a protein possesses a specific structural or functional feature, such as a domain, motif, or modification site.
-
E.
isAbundantInFood
Indicates that a particular nutrient, substance, or component is present in large quantities within a given food.
- 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_69c68a625d048190af70eb8b63bec5a0 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f303eb988190ba9df7946fce1c86 |
completed | March 27, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69c6f03648d08190b862d07fef71210c |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:12 p.m.