Triple
T1477732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Jordan |
E30880
|
entity |
| Predicate | endorsedBrand |
P18857
|
FINISHED |
| Object | Gatorade |
E82561
|
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: Gatorade | Statement: [Michael Jordan, endorsedBrand, Gatorade]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gatorade Context triple: [Michael Jordan, endorsedBrand, Gatorade]
-
A.
Gatorade
chosen
Gatorade is a popular sports drink brand owned by PepsiCo, widely used by athletes and closely associated with professional sports.
-
B.
Powerade
Powerade is a sports drink brand known for its electrolyte-enhanced beverages designed to help athletes rehydrate and replenish energy during physical activity.
-
C.
P-Cola
P-Cola is a common shorthand nickname for the city of Pensacola in the Florida Panhandle.
-
D.
Fanta
Fanta is a globally popular fruit-flavored soft drink brand known for its bright colors and wide variety of flavors.
-
E.
Coca-Cola Zero Sugar
Coca-Cola Zero Sugar is a no-calorie soft drink introduced by The Coca-Cola Company as a sugar-free alternative that closely mimics the taste of original Coca-Cola.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a498fe55a88190ab7f9e40ace88e49 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c605d4c0819088ab06678b2ba6f3 |
completed | March 1, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad15add78c8190843efd75bbe8423f |
completed | March 8, 2026, 6:22 a.m. |
Created at: March 1, 2026, 8:11 p.m.