Triple
T26508221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Bull White Edition Coconut Berry |
E669608
|
entity |
| Predicate | containsStimulant |
P184836
|
FINISHED |
| Object | caffeine |
—
|
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: caffeine | Statement: [Red Bull White Edition Coconut Berry, containsStimulant, caffeine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsStimulant Context triple: [Red Bull White Edition Coconut Berry, containsStimulant, caffeine]
-
A.
hasAddictiveSubstance
Indicates that an entity contains or involves a substance capable of causing addiction in those who use or consume it.
-
B.
containsNicotine
Indicates that the subject has nicotine as one of its components or ingredients.
-
C.
isPsychoactive
Indicates that a substance or agent has effects on the mind or nervous system that can alter perception, mood, consciousness, cognition, or behavior.
-
D.
containsAlkaloids
Indicates that a substance, organism, or material has alkaloid compounds present within it.
-
E.
hasAddictionPotential
Indicates that one entity (typically a substance or activity) has the capacity to cause another entity (typically a person) to develop dependence or addictive behavior toward it.
- 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_69eeb319ec70819090834c2591cf5f1e |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f7b628b17c8190aa058c1a51852a27 |
completed | May 3, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c06f5881908f0b98cad6796478 |
completed | May 3, 2026, 8:49 p.m. |
| PDg | Predicate description generation | batch_69f7b5cadd308190a864245a21b08f9a |
completed | May 3, 2026, 8:53 p.m. |
Created at: April 27, 2026, 1:18 a.m.