Triple
T32976950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aston Martin Vantage |
E843690
|
entity |
| Predicate | notableVariant |
P4680
|
FINISHED |
| Object |
Vantage N24
The Vantage N24 is a track-focused racing version of the Aston Martin V8 Vantage, developed for endurance events like the Nürburgring 24 Hours.
|
E2030021
|
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: Vantage N24 | Statement: [Aston Martin Vantage, notableVariant, Vantage N24]
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: Vantage N24 Triple: [Aston Martin Vantage, notableVariant, Vantage N24]
Generated description
The Vantage N24 is a track-focused racing version of the Aston Martin V8 Vantage, developed for endurance events like the Nürburgring 24 Hours.
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_69f3494b9fc48190bb61c955ba471275 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d1d916f881909575c2b22c416a5b |
completed | May 3, 2026, 4:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a34d28695e88190bc50683f9c971fbf |
completed | June 19, 2026, 5:24 a.m. |
| NEDg | Description generation | batch_6a34d35803148190815cb96805ce4ba0 |
completed | June 19, 2026, 5:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a34d423fc108190aeb3f93fbabdf591 |
completed | June 19, 2026, 5:31 a.m. |
Created at: May 1, 2026, 1:22 a.m.