Triple
T11292683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shaun White |
E267365
|
entity |
| Predicate | sponsoredBy |
P67
|
FINISHED |
| Object |
Oakley (former)
Oakley (former) is a sports performance and lifestyle brand best known for its high-tech eyewear, apparel, and accessories popular among professional athletes and outdoor enthusiasts.
|
E915709
|
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: Oakley (former) | Statement: [Shaun White, sponsoredBy, Oakley (former)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oakley (former) Context triple: [Shaun White, sponsoredBy, Oakley (former)]
-
A.
Oakley
Oakley is a city in Contra Costa County, California, located in the eastern San Francisco Bay Area.
-
B.
Oakley
Oakley is a surname most notably associated with Violet Oakley, an American artist and pioneering female muralist of the early 20th century.
-
C.
Koss
Koss is a Norwegian surname most notably associated with Johann Olav Koss, the Olympic gold medal–winning speed skater and humanitarian.
-
D.
K2 Sports
K2 Sports is an American sporting goods company best known for its skis, snowboards, and other winter sports equipment.
-
E.
Blue Ribbon Sports
Blue Ribbon Sports was the original name of the company that later became Nike, Inc., the global athletic footwear and apparel giant.
- 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: Oakley (former) Triple: [Shaun White, sponsoredBy, Oakley (former)]
Generated description
Oakley (former) is a sports performance and lifestyle brand best known for its high-tech eyewear, apparel, and accessories popular among professional athletes and outdoor enthusiasts.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Oakley (former) Target entity description: Oakley (former) is a sports performance and lifestyle brand best known for its high-tech eyewear, apparel, and accessories popular among professional athletes and outdoor enthusiasts.
-
A.
Oakley
Oakley is a city in Contra Costa County, California, located in the eastern San Francisco Bay Area.
-
B.
Oakley
Oakley is a surname most notably associated with Violet Oakley, an American artist and pioneering female muralist of the early 20th century.
-
C.
Koss
Koss is a Norwegian surname most notably associated with Johann Olav Koss, the Olympic gold medal–winning speed skater and humanitarian.
-
D.
K2 Sports
K2 Sports is an American sporting goods company best known for its skis, snowboards, and other winter sports equipment.
-
E.
Blue Ribbon Sports
Blue Ribbon Sports was the original name of the company that later became Nike, Inc., the global athletic footwear and apparel giant.
- 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e989fdac81909a4a75f1f68b55c6 |
completed | April 9, 2026, 6:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4f4a57d6881909a1e65744111ad8b |
completed | April 19, 2026, 3:28 p.m. |
| NEDg | Description generation | batch_69e4f95cbc7c819082e3d7c3c3266708 |
completed | April 19, 2026, 3:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4ff73f3348190abfd28f716c61105 |
completed | April 19, 2026, 4:14 p.m. |
Created at: April 8, 2026, 9:32 p.m.