Triple
T11731197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ploom TECH |
E278899
|
entity |
| Predicate | regulatoryCategoryInJapan |
P62860
|
FINISHED |
| Object | tobacco product |
—
|
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: tobacco product | Statement: [Ploom TECH, regulatoryCategoryInJapan, tobacco product]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regulatoryCategoryInJapan Context triple: [Ploom TECH, regulatoryCategoryInJapan, tobacco product]
-
A.
legalClassificationInJapan
chosen
Indicates how something is categorized or defined under Japanese law.
-
B.
regulatoryType
Indicates the specific kind or category of regulatory control, rule, or oversight that applies in the given relationship.
-
C.
certificationJapan
Indicates that an entity holds or is associated with a certification that is specific to or recognized in Japan.
-
D.
regulatedIn
Indicates that one entity’s activity, expression, or occurrence is controlled, influenced, or modulated by another entity within a specific context or system.
-
E.
regulationStatus
Indicates the regulatory condition or compliance state that applies to an entity under relevant rules or laws.
- 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_69d6aaffec6881908bead509e8621742 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4d94de08190a7184cf26d8cb94e |
completed | April 10, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69d88a7f51248190bf492bd7509b5413 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.