Triple

T32608154
Position Surface form Disambiguated ID Type / Status
Subject Lamborghini Museum E833578 entity
Predicate hasExhibit P35 FINISHED
Object Lamborghini Huracán
The Lamborghini Huracán is a high-performance Italian supercar known for its aggressive design, naturally aspirated V10 engine, and advanced all-wheel-drive technology.
E1183285 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: Lamborghini Huracán | Statement: [Lamborghini Museum, hasExhibit, Lamborghini Huracán]
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: Lamborghini Huracán
Triple: [Lamborghini Museum, hasExhibit, Lamborghini Huracán]
Generated description
The Lamborghini Huracán is a high-performance Italian supercar known for its aggressive design, naturally aspirated V10 engine, and advanced all-wheel-drive technology.

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_69f3492bfa648190b6ae472074634e29 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6c6c80a388190b038cfe32c2f2ca4 completed May 3, 2026, 3:53 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34b14d299481908e583b94bb903d1f completed June 19, 2026, 3:02 a.m.
NEDg Description generation batch_6a34b20dec888190920a1472083382c0 completed June 19, 2026, 3:05 a.m.
NED2 Entity disambiguation (via description) batch_6a34b2b0f36c8190ab30af3d30024b97 completed June 19, 2026, 3:08 a.m.
Created at: May 1, 2026, 1:05 a.m.