Triple

T32976952
Position Surface form Disambiguated ID Type / Status
Subject Aston Martin Vantage E843690 entity
Predicate notableVariant P4680 FINISHED
Object Vantage GTE
The Vantage GTE is Aston Martin’s race-spec version of the Vantage, engineered for endurance competition in the FIA World Endurance Championship and the 24 Hours of Le Mans.
E2031510 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 GTE | Statement: [Aston Martin Vantage, notableVariant, Vantage GTE]
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 GTE
Triple: [Aston Martin Vantage, notableVariant, Vantage GTE]
Generated description
The Vantage GTE is Aston Martin’s race-spec version of the Vantage, engineered for endurance competition in the FIA World Endurance Championship and the 24 Hours of Le Mans.

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_6a34dabba3f48190a95eed6422cc1f7e completed June 19, 2026, 5:59 a.m.
NEDg Description generation batch_6a34db4fc32c8190a2277b24a9031669 completed June 19, 2026, 6:01 a.m.
NED2 Entity disambiguation (via description) batch_6a34dbec0c9c8190ac5b263151322aba completed June 19, 2026, 6:04 a.m.
Created at: May 1, 2026, 1:22 a.m.