Triple
T30790995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volkswagen Group C platform |
E784093
|
entity |
| Predicate | usedInModel |
P25490
|
FINISHED |
| Object |
Audi A6 C8
The Audi A6 C8 is the fifth-generation mid-size luxury executive sedan from Audi, featuring advanced driver assistance technologies, efficient powertrains, and a high-tech, minimalist interior design.
|
E1931839
|
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 A6 C8 | Statement: [Volkswagen Group C platform, usedInModel, Audi A6 C8]
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 A6 C8 Triple: [Volkswagen Group C platform, usedInModel, Audi A6 C8]
Generated description
The Audi A6 C8 is the fifth-generation mid-size luxury executive sedan from Audi, featuring advanced driver assistance technologies, efficient powertrains, and a high-tech, minimalist interior design.
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_69f224b2e2a48190b19aa43db9da5b67 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6900dbd908190baf39dd5cf37d619 |
completed | May 3, 2026, midnight |
| NED1 | Entity disambiguation (via context triple) | batch_6a28b0ab99dc8190b9abc5c621011d9f |
completed | June 10, 2026, 12:32 a.m. |
| NEDg | Description generation | batch_6a28b4c2ef9881909dc874a55878a70d |
completed | June 10, 2026, 12:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a28b563bb8081909a24f086f105b85d |
completed | June 10, 2026, 12:52 a.m. |
Created at: April 29, 2026, 8:42 p.m.