Triple

T27842407
Position Surface form Disambiguated ID Type / Status
Subject Clos Saint-Denis E703718 entity
Predicate governingAOC P94604 FINISHED
Object Clos Saint-Denis AOC
Clos Saint-Denis AOC is a prestigious Grand Cru wine appellation in Burgundy’s Côte de Nuits, renowned for producing elegant, complex red wines primarily from Pinot Noir.
E1792295 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: Clos Saint-Denis AOC | Statement: [Clos Saint-Denis, governingAOC, Clos Saint-Denis AOC]
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: Clos Saint-Denis AOC
Triple: [Clos Saint-Denis, governingAOC, Clos Saint-Denis AOC]
Generated description
Clos Saint-Denis AOC is a prestigious Grand Cru wine appellation in Burgundy’s Côte de Nuits, renowned for producing elegant, complex red wines primarily from Pinot Noir.

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_69ef840d9e3c819093615ebff4ec22be completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f638d75ba48190bfd2a602f4c5361a completed May 2, 2026, 5:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12f734f8488190a8049055a6e5d06b completed May 24, 2026, 1:03 p.m.
NEDg Description generation batch_6a12f7ba8f048190ac484434da112aeb completed May 24, 2026, 1:06 p.m.
NED2 Entity disambiguation (via description) batch_6a12fb5822408190812399cb2a623e74 completed May 24, 2026, 1:21 p.m.
Created at: April 27, 2026, 6:04 p.m.