Triple

T6000659
Position Surface form Disambiguated ID Type / Status
Subject The Best a Man Can Get E133585 entity
Predicate promotesBrand P61924 FINISHED
Object Gillette shaving products 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: Gillette shaving products | Statement: [The Best a Man Can Get, promotesBrand, Gillette shaving products]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gillette shaving products
Context triple: [The Best a Man Can Get, promotesBrand, Gillette shaving products]
  • A. Gillette chosen
    Gillette is a globally recognized American brand best known for its razors and shaving products.
  • B. Braun
    Braun is a German surname most infamously associated with Eva Braun, the longtime companion and brief wife of Adolf Hitler.
  • C. Shaver
    Shaver is the middle name of James Shaver Woodsworth, a prominent Canadian social reformer and founding leader of the Co-operative Commonwealth Federation.
  • D. Garnier
    Garnier is a French surname most famously associated with architect Charles Garnier, designer of the Paris Opéra.
  • E. Brillo
    Brillo is a lightweight, Android-based operating system developed by Google for powering and managing Internet of Things (IoT) devices.
  • 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_69c0560bae148190ad4755defaaf471b completed March 22, 2026, 8:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1413ca5f88190b0dab30bde04af4c completed March 23, 2026, 1:33 p.m.
Created at: March 22, 2026, 4:05 p.m.