Triple

T35516188
Position Surface form Disambiguated ID Type / Status
Subject Caiño Blanco E1026424 entity
Predicate oenologicalInterest P17953 FINISHED
Object valued for freshness and structure 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: valued for freshness and structure | Statement: [Caiño Blanco, oenologicalInterest, valued for freshness and structure]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: oenologicalInterest
Context triple: [Caiño Blanco, oenologicalInterest, valued for freshness and structure]
  • A. oenologicalSignificance chosen
    Indicates the relationship in which something holds importance, relevance, or notable impact within the context of wine or winemaking.
  • B. oenologicalPractice
    Indicates a relationship where an entity is involved in, applies, or is characterized by a specific winemaking or wine-handling practice.
  • C. wineLaw
    Indicates a legal or regulatory relationship governing the production, sale, labeling, or distribution of wine.
  • D. oenologist
    Indicates that one entity is an expert in the science and practice of wine and winemaking in relation to another entity.
  • E. oenologicalProperty
    Indicates a relationship where a characteristic or attribute is specifically related to wine or the science of winemaking.
  • 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_69f76dfe78b081908e2b14cb88dd8c00 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79a54aa3c8190b2bb5d790b2d42d4 completed May 3, 2026, 6:56 p.m.
PD Predicate disambiguation batch_69f7961970408190b669cc556e30a608 completed May 3, 2026, 6:38 p.m.
Created at: May 3, 2026, 4:04 p.m.