Triple
T9010130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lamborghini Urus |
E215445
|
entity |
| Predicate | driveModes |
P85075
|
FINISHED |
| Object |
Neve
Neve is a specialized driving mode in the Lamborghini Urus optimized for enhanced traction and stability on snow and low-grip surfaces.
|
E773442
|
NE FINISHED |
How this triple was built (4 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: Neve | Statement: [Lamborghini Urus, driveModes, Neve]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neve Context triple: [Lamborghini Urus, driveModes, Neve]
-
A.
Neve
Neve is one of the official mascots of the 2006 Winter Olympics in Turin, depicted as a stylized snowball symbolizing winter sports and the spirit of the Games.
-
B.
Nieves
Nieves is a Spanish-language surname commonly found in Puerto Rico and other Spanish-speaking regions.
-
C.
Ice Mountain
Ice Mountain is a regional bottled water brand in the United States known for its spring water sourced from Midwestern aquifers.
-
D.
Tennenlohe
Tennenlohe is a district of Erlangen in Bavaria, Germany, known for its proximity to research institutions and the Tennenlohe Forest nature reserve.
-
E.
Black Glacier
Black Glacier is a mountain glacier located on the slopes of Mount Olympus in Washington's Olympic Mountains.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Neve Triple: [Lamborghini Urus, driveModes, Neve]
Generated description
Neve is a specialized driving mode in the Lamborghini Urus optimized for enhanced traction and stability on snow and low-grip surfaces.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Neve Target entity description: Neve is a specialized driving mode in the Lamborghini Urus optimized for enhanced traction and stability on snow and low-grip surfaces.
-
A.
Neve
Neve is one of the official mascots of the 2006 Winter Olympics in Turin, depicted as a stylized snowball symbolizing winter sports and the spirit of the Games.
-
B.
Nieves
Nieves is a Spanish-language surname commonly found in Puerto Rico and other Spanish-speaking regions.
-
C.
Ice Mountain
Ice Mountain is a regional bottled water brand in the United States known for its spring water sourced from Midwestern aquifers.
-
D.
Tennenlohe
Tennenlohe is a district of Erlangen in Bavaria, Germany, known for its proximity to research institutions and the Tennenlohe Forest nature reserve.
-
E.
Black Glacier
Black Glacier is a mountain glacier located on the slopes of Mount Olympus in Washington's Olympic Mountains.
- F. None of above. chosen
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_69ca83a2bf088190986ee7a8eb90407d |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc69c00ae8819090786385a72e8baf |
completed | April 1, 2026, 12:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfdb9a11948190a43f60d0df71b1af |
completed | April 3, 2026, 3:24 p.m. |
| NEDg | Description generation | batch_69cfdd80d5ac8190862704a62ac1c942 |
completed | April 3, 2026, 3:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfde1eb8588190859a015f61d8f433 |
completed | April 3, 2026, 3:34 p.m. |
Created at: March 30, 2026, 7:06 p.m.