Triple

T14387566
Position Surface form Disambiguated ID Type / Status
Subject Crljenak Kaštelanski E356764 entity
Predicate alcoholPotential P112051 FINISHED
Object high 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: high | Statement: [Crljenak Kaštelanski, alcoholPotential, high]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: alcoholPotential
Context triple: [Crljenak Kaštelanski, alcoholPotential, high]
  • A. wineAlcoholPotential chosen
    Indicates the potential alcohol content that a wine could reach based on its current sugar level or fermentation stage.
  • B. madeWithAlcohol
    Indicates that something is created, prepared, or produced using alcohol as an ingredient or component.
  • C. alcoholType
    Indicates the specific kind or category of alcohol associated with an entity (e.g., beer, wine, spirits).
  • D. alcoholRange
    Indicates the range or interval of alcohol content associated with an entity (e.g., minimum and maximum alcohol level).
  • E. alcoholLevel
    Indicates the measured concentration or amount of alcohol present in an entity (such as a person, substance, or environment).
  • 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_69d827927c988190ad98bb0360981783 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de90283b9c8190b50d30ad58bfe085 completed April 14, 2026, 7:06 p.m.
PD Predicate disambiguation batch_69de2aa024c48190805df6a9d63deb10 completed April 14, 2026, 11:53 a.m.
Created at: April 10, 2026, 1:16 a.m.