Triple
T27729352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monster Energy |
E697388
|
entity |
| Predicate | typicalCaffeineContentPer473mlCan |
P38318
|
FINISHED |
| Object | about 160 mg |
—
|
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: about 160 mg | Statement: [Monster Energy, typicalCaffeineContentPer473mlCan, about 160 mg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCaffeineContentPer473mlCan Context triple: [Monster Energy, typicalCaffeineContentPer473mlCan, about 160 mg]
-
A.
hasCaffeineContent
chosen
Indicates that one entity (typically a beverage or substance) possesses a specified amount or presence of caffeine.
-
B.
typicalCaffeineSource
Indicates that one entity is a common or characteristic source from which the other entity typically obtains caffeine.
-
C.
isSoftDrinkVariantOf
Indicates that one soft drink is a specific version, flavor, or formulation derived from or based on another soft drink.
-
D.
isColaBrandOf
Indicates that a given brand is a cola-type soft drink brand belonging to or produced by a specified company or entity.
-
E.
canBeCarbonated
Indicates that the subject is capable of being made carbonated, typically by dissolving carbon dioxide under pressure.
- 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_69ef590c3e288190ad54d2465af8ca4e |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69fff86e544c81908063f61b876c9d78 |
completed | May 10, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69fff7e7cb688190977eeca41aad25b9 |
completed | May 10, 2026, 3:13 a.m. |
Created at: April 27, 2026, 3:10 p.m.