Triple

T32622584
Position Surface form Disambiguated ID Type / Status
Subject Volkswagen Golf Cabriolet E833968 entity
Predicate platform P1292 FINISHED
Object Volkswagen PQ35 platform
The Volkswagen PQ35 platform is a modular automotive architecture used by Volkswagen Group for various compact and mid-size front-engine, front- or all-wheel-drive vehicles across multiple brands.
E742844 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: Volkswagen PQ35 platform | Statement: [Volkswagen Golf Cabriolet, platform, Volkswagen PQ35 platform]
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: Volkswagen PQ35 platform
Triple: [Volkswagen Golf Cabriolet, platform, Volkswagen PQ35 platform]
Generated description
The Volkswagen PQ35 platform is a modular automotive architecture used by Volkswagen Group for various compact and mid-size front-engine, front- or all-wheel-drive vehicles across multiple brands.

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_69f3492ccc80819086ef7d26e9786647 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6c6f0a8e08190a7d8f6e7c77b59bd completed May 3, 2026, 3:54 a.m.
NED1 Entity disambiguation (via context triple) batch_6a349eaae3e88190975e0e53906008ce completed June 19, 2026, 1:43 a.m.
NEDg Description generation batch_6a349f7f7c1c81908cf908084632c815 completed June 19, 2026, 1:46 a.m.
NED2 Entity disambiguation (via description) batch_6a34a0220314819091450074e783e841 completed June 19, 2026, 1:49 a.m.
Created at: May 1, 2026, 1:06 a.m.