Triple

T8418383
Position Surface form Disambiguated ID Type / Status
Subject Speed Stick Antiperspirant E198784 entity
Predicate regulatoryClass P14058 FINISHED
Object cosmetic in many markets 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: cosmetic in many markets | Statement: [Speed Stick Antiperspirant, regulatoryClass, cosmetic in many markets]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: regulatoryClass
Context triple: [Speed Stick Antiperspirant, regulatoryClass, cosmetic in many markets]
  • A. regulatoryType chosen
    Indicates the specific kind or category of regulatory control, rule, or oversight that applies in the given relationship.
  • B. regulationStatus
    Indicates the regulatory condition or compliance state that applies to an entity under relevant rules or laws.
  • C. regulatorType
    Indicates the specific kind or category of regulatory role or authority associated with an entity.
  • D. regulatoryField
    Indicates that one entity operates within, is governed by, or is associated with a particular area or domain of regulation defined by another entity.
  • E. regulatoryStandard
    Indicates that one entity serves as an official rule, guideline, or benchmark that governs, constrains, or evaluates the behavior, quality, or performance of 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_69ca8312d63c8190bf133b676b44a385 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb84c7d6e48190a2bbde89c5d42af6 completed March 31, 2026, 8:24 a.m.
PD Predicate disambiguation batch_69cb70d70ea081909c3dc1bd2ec14f85 completed March 31, 2026, 6:59 a.m.
Created at: March 30, 2026, 6:06 p.m.