Triple

T4322588
Position Surface form Disambiguated ID Type / Status
Subject Pressac E96552 entity
Predicate typicalWineTanninLevel P2069 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: [Pressac, typicalWineTanninLevel, high]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typicalWineTanninLevel
Context triple: [Pressac, typicalWineTanninLevel, high]
  • A. tanninLevel chosen
    Indicates the degree or intensity of tannins present in or associated with something, typically a beverage like wine or tea.
  • B. wineStyle
    Indicates the stylistic category or type of wine (such as its production style, sweetness, body, or other defining characteristics) associated with an entity.
  • C. traditionalGrapeVariety
    Indicates that a grape variety is traditionally or historically used in a specific region, wine style, or cultural winemaking practice.
  • D. wineColor
    Indicates the color attribute or hue associated with a given wine.
  • E. wineCharacteristic
    Indicates a descriptive property or quality attributed to a wine, such as its flavor, aroma, color, or style.
  • 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_69b345422aac81909ddbadae437d122e completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b351177eb88190b89fa49a88add5e8 completed March 12, 2026, 11:49 p.m.
PD Predicate disambiguation batch_69b34f4bec888190987fc2631498b637 completed March 12, 2026, 11:42 p.m.
Created at: March 12, 2026, 11:12 p.m.