Triple

T2717656
Position Surface form Disambiguated ID Type / Status
Subject Angostura bitters E60005 entity
Predicate alcoholByVolume P2071 FINISHED
Object 44.7% 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: 44.7% | Statement: [Angostura bitters, alcoholByVolume, 44.7%]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: alcoholByVolume
Context triple: [Angostura bitters, alcoholByVolume, 44.7%]
  • A. alcoholType
    Indicates the specific kind or category of alcohol associated with an entity (e.g., beer, wine, spirits).
  • B. alcoholLevel chosen
    Indicates the measured concentration or amount of alcohol present in an entity (such as a person, substance, or environment).
  • C. madeWithAlcohol
    Indicates that something is created, prepared, or produced using alcohol as an ingredient or component.
  • D. servesAlcohol
    Indicates that an establishment or provider offers and supplies alcoholic beverages to customers or participants.
  • E. traditionalDrink
    Indicates that one entity is a beverage customarily consumed within the culture, heritage, or longstanding practices associated with 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_69ab4b746d248190958e052045c09255 completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdaad577c8190819d3c641c2406f4 completed March 7, 2026, 7:58 a.m.
PD Predicate disambiguation batch_69abd8240920819087a812d816a55edb completed March 7, 2026, 7:47 a.m.
Created at: March 6, 2026, 9:55 p.m.