Triple

T2190472
Position Surface form Disambiguated ID Type / Status
Subject Listerine E49848 entity
Predicate hasVariant P455 FINISHED
Object Listerine Naturals E49848 NE 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: Listerine Naturals | Statement: [Listerine, hasVariant, Listerine Naturals]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Listerine Naturals
Context triple: [Listerine, hasVariant, Listerine Naturals]
  • A. Colgate-Palmolive
    Colgate-Palmolive is a global consumer products company best known for its oral care, personal care, home care, and pet nutrition brands.
  • B. Listerine chosen
    Listerine is a widely used antiseptic mouthwash brand known for its strong flavor and plaque- and germ-fighting oral care products.
  • C. Kellex Corporation
    Kellex Corporation was an engineering firm best known for designing and overseeing construction of the K-25 gaseous diffusion plant used in the Manhattan Project to enrich uranium during World War II.
  • D. Procter & Gamble
    Procter & Gamble is a multinational consumer goods corporation known for a wide range of household, personal care, and hygiene brands sold globally.
  • E. Johnson & Johnson
    Johnson & Johnson is a multinational healthcare conglomerate best known for its pharmaceuticals, medical devices, and consumer health products.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69a88aaba3c48190b351cab9b26989ff completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abbf3f5e008190beda3ce5d77209e0 completed March 7, 2026, 6:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5db0352c8190aa9c4c58460df3a4 completed March 9, 2026, 5:42 a.m.
Created at: March 4, 2026, 7:46 p.m.