Triple
T1220896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LeBron James |
E26218
|
entity |
| Predicate | endorsedBrand |
P18857
|
FINISHED |
| Object | Coca-Cola |
E90215
|
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: Coca-Cola | Statement: [LeBron James, endorsedBrand, Coca-Cola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Coca-Cola Context triple: [LeBron James, endorsedBrand, Coca-Cola]
-
A.
Coca-Cola
chosen
Coca-Cola is a globally recognized carbonated soft drink, known for its distinctive cola flavor and iconic red-and-white branding.
-
B.
The Coca-Cola Company
The Coca-Cola Company is a multinational beverage corporation best known as the producer of the iconic soft drink Coca-Cola and a wide portfolio of nonalcoholic beverages sold worldwide.
-
C.
Pepsi
Pepsi is a globally recognized carbonated soft drink brand produced by PepsiCo and known as one of the main competitors to Coca-Cola.
-
D.
PepsiCo
PepsiCo is a multinational food, snack, and beverage corporation best known for producing the Pepsi soft drink and a wide portfolio of global consumer brands.
-
E.
Coca-Cola FEMSA
Coca-Cola FEMSA is the largest franchise bottler of Coca-Cola products in the world, operating extensive beverage production and distribution networks across Latin America and parts of Asia.
- 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_69a49484688c8190a1bf285eb396a8b6 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf169868819090cfab7e34c40c67 |
completed | March 1, 2026, 10:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acacaf11588190b0bbc1d280bf9a78 |
completed | March 7, 2026, 10:54 p.m. |
Created at: March 1, 2026, 7:46 p.m.