Triple
T7893718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monster |
E183296
|
entity |
| Predicate | hasRegulatoryConcern |
P31131
|
FINISHED |
| Object | high caffeine content |
—
|
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: high caffeine content | Statement: [Monster, hasRegulatoryConcern, high caffeine content]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegulatoryConcern Context triple: [Monster, hasRegulatoryConcern, high caffeine content]
-
A.
regulatoryIssues
chosen
Indicates that there are regulatory concerns, non-compliance, or potential violations associated with the related entity or activity.
-
B.
regulationAtIssue
Indicates that a specific regulation is the subject of concern, dispute, or analysis in the given context.
-
C.
hasRegulations
Indicates that one entity imposes, contains, or is associated with rules or regulatory requirements that govern the behavior or operation of another entity.
-
D.
associatedWithRegulation
Indicates a relationship where something is linked to, governed by, or relevant to a specific regulation or regulatory framework.
-
E.
hasRegulatedBy
Indicates that one entity is subject to control, governance, or rules imposed by another entity.
- 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_69ca828c474c8190a254d6499871eaff |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a008fb88190a039fec40483ab93 |
completed | March 31, 2026, 3:05 a.m. |
| PD | Predicate disambiguation | batch_69cae92d94448190b4425bbfb64c658c |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:01 p.m.