Triple

T21906684
Position Surface form Disambiguated ID Type / Status
Subject Vaccarèse E540958 entity
Predicate oenologicalRole P17953 FINISHED
Object adds color to blends 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: adds color to blends | Statement: [Vaccarèse, oenologicalRole, adds color to blends]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: oenologicalRole
Context triple: [Vaccarèse, oenologicalRole, adds color to blends]
  • A. oenologist
    Indicates that one entity is an expert in the science and practice of wine and winemaking in relation to another entity.
  • B. oenologicalPractice
    Indicates a relationship where an entity is involved in, applies, or is characterized by a specific winemaking or wine-handling practice.
  • C. viticulturalRole
    Indicates the specific function, responsibility, or involvement an entity has within viticulture or grape-growing activities.
  • D. oenologicalSignificance chosen
    Indicates the relationship in which something holds importance, relevance, or notable impact within the context of wine or winemaking.
  • E. wineEconomyRole
    Indicates the role or function an entity has within the wine-related economy, such as production, distribution, trade, or regulation.
  • 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_69e0c47b4e8c81908c8076eaa4c8e4f2 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f121d74d388190be58b937c486fa69 completed April 28, 2026, 9:08 p.m.
PD Predicate disambiguation batch_69e6be9ebf4c8190892df1a8e1313f88 completed April 21, 2026, 12:02 a.m.
Created at: April 16, 2026, 7:38 p.m.