Triple

T33053555
Position Surface form Disambiguated ID Type / Status
Subject Sula Brut E845791 entity
Predicate fermentationMethod P14597 FINISHED
Object Charmat method
The Charmat method is a sparkling wine production technique in which the second fermentation occurs in large pressurized tanks, typically yielding fresh, fruit-forward wines.
E2034423 NE 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: Charmat method | Statement: [Sula Brut, fermentationMethod, Charmat method]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Charmat method
Triple: [Sula Brut, fermentationMethod, Charmat method]
Generated description
The Charmat method is a sparkling wine production technique in which the second fermentation occurs in large pressurized tanks, typically yielding fresh, fruit-forward wines.

Provenance (5 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_69f3495242e48190996a2cb2beab5455 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d34152e88190938096818075bee0 completed May 3, 2026, 4:46 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34e51e273c81908ee360c0d6adc183 completed June 19, 2026, 6:43 a.m.
NEDg Description generation batch_6a34e60ea2148190aca7cc32e7d2b9d9 completed June 19, 2026, 6:47 a.m.
NED2 Entity disambiguation (via description) batch_6a34e6d01ce08190b4edfcda322afae0 completed June 19, 2026, 6:50 a.m.
Created at: May 1, 2026, 1:24 a.m.