Triple

T5606874
Position Surface form Disambiguated ID Type / Status
Subject Dark and Lovely E147253 entity
Predicate formulationFocus P3660 FINISHED
Object conditioning ingredients 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: conditioning ingredients | Statement: [Dark and Lovely, formulationFocus, conditioning ingredients]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: formulationFocus
Context triple: [Dark and Lovely, formulationFocus, conditioning ingredients]
  • A. coFormulated
    Indicates that two or more entities were jointly formulated, designed, or created together as part of the same process or product.
  • B. formulatedIn
    Indicates that something was created, developed, or expressed within a particular context, place, or framework.
  • C. hasFormulation chosen
    Indicates that one entity is expressed, prepared, or configured in a particular form or composition defined by another entity.
  • D. brandFocus
    Indicates that a brand primarily concentrates its efforts, messaging, or resources on a particular target, theme, or market segment.
  • E. focusType
    Indicates the specific kind or category of focus or attention that is being applied to or associated with an entity or interaction.
  • 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_69c0090500f881908374285baf0ac46f completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c020fbb8748190841e5e09db3feef1 completed March 22, 2026, 5:03 p.m.
PD Predicate disambiguation batch_69c01b1b3c98819080687d18ab10a914 completed March 22, 2026, 4:38 p.m.
Created at: March 22, 2026, 3:39 p.m.