Triple

T704751
Position Surface form Disambiguated ID Type / Status
Subject Mount Veeder AVA E14074 entity
Predicate viticultureCharacteristic P9793 FINISHED
Object low yields 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: low yields | Statement: [Mount Veeder AVA, viticultureCharacteristic, low yields]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: viticultureCharacteristic
Context triple: [Mount Veeder AVA, viticultureCharacteristic, low yields]
  • A. viticulturalCharacteristic chosen
    Indicates a relationship where a specific trait, quality, or property is attributed to viticulture or grape-growing practices.
  • B. viticulturalFocus
    Indicates a focus on or specialization in viticulture, i.e., activities, practices, or interests centered on grape growing and vineyard management.
  • C. viticulturalChallenge
    Indicates a relationship where one party faces or presents a difficulty, problem, or obstacle specifically related to grape growing or vineyard management.
  • D. primaryGrapeVariety
    Indicates that one entity is the main or predominant grape variety used in producing the other entity (typically a wine or wine-based product).
  • 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_69a493494ec48190ae6751683625a9ba completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a58d4c3c8190ad4527d14bca5e6e completed March 1, 2026, 8:46 p.m.
PD Predicate disambiguation batch_69a4a4edc33881909a978268f6dd5d82 completed March 1, 2026, 8:43 p.m.
Created at: March 1, 2026, 7:36 p.m.