Triple

T6000666
Position Surface form Disambiguated ID Type / Status
Subject The Best a Man Can Get E133585 entity
Predicate associatedWithCompany P629 FINISHED
Object The Gillette Company E24830 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: The Gillette Company | Statement: [The Best a Man Can Get, associatedWithCompany, The Gillette Company]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Gillette Company
Context triple: [The Best a Man Can Get, associatedWithCompany, The Gillette Company]
  • A. Gillette chosen
    Gillette is a globally recognized American brand best known for its razors and shaving products.
  • B. Procter & Gamble
    Procter & Gamble is a multinational consumer goods corporation known for a wide range of household, personal care, and hygiene brands sold globally.
  • C. Colgate-Palmolive
    Colgate-Palmolive is a global consumer products company best known for its oral care, personal care, home care, and pet nutrition brands.
  • D. Johnson & Johnson
    Johnson & Johnson is a multinational healthcare conglomerate best known for its pharmaceuticals, medical devices, and consumer health products.
  • E. Kimberly-Clark Corporation
    Kimberly-Clark Corporation is a multinational personal care company best known for brands such as Kleenex, Huggies, and Scott paper 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_69c00872444c8190bfaf1739dcec765c completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04ee7c0e08190a6e78969448b070a completed March 22, 2026, 8:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20d3a18e4819081b6f3c5a1f02b25 completed March 24, 2026, 4:04 a.m.
Created at: March 22, 2026, 4:05 p.m.