Triple

T35887121
Position Surface form Disambiguated ID Type / Status
Subject Volkswagen Forest plant E1037678 entity
Predicate currentProduct P200251 FINISHED
Object Audi Q8 Sportback e-tron
The Audi Q8 Sportback e-tron is a premium all-electric coupe-style SUV that combines Audi’s luxury features with a sleek fastback design and zero-emission performance.
E2168220 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: Audi Q8 Sportback e-tron | Statement: [Volkswagen Forest plant, currentProduct, Audi Q8 Sportback e-tron]
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: Audi Q8 Sportback e-tron
Triple: [Volkswagen Forest plant, currentProduct, Audi Q8 Sportback e-tron]
Generated description
The Audi Q8 Sportback e-tron is a premium all-electric coupe-style SUV that combines Audi’s luxury features with a sleek fastback design and zero-emission performance.

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_69f76e1f4d748190bb55594d8441d70e completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69ff7d01cb808190be47f9ab44e552df completed May 9, 2026, 6:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38d5247cc88190bd87a8fa366c0bf7 completed June 22, 2026, 6:24 a.m.
NEDg Description generation batch_6a38d58d00c48190b675fee8bef79411 completed June 22, 2026, 6:26 a.m.
NED2 Entity disambiguation (via description) batch_6a38d681cf388190896a30e2b0939181 completed June 22, 2026, 6:30 a.m.
Created at: May 3, 2026, 4:06 p.m.