Triple
T22663198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leo Burnett Worldwide |
E559715
|
entity |
| Predicate | hasNotableClient |
P7186
|
FINISHED |
| Object | Kellogg’s |
—
|
NE NERFINISHED |
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: Kellogg’s | Statement: [Leo Burnett Worldwide, hasNotableClient, Kellogg’s]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kellogg’s Context triple: [Leo Burnett Worldwide, hasNotableClient, Kellogg’s]
-
A.
Kellogg Company
chosen
Kellogg Company is a major American multinational food manufacturing company best known for its breakfast cereals and convenience foods.
-
B.
Postum Cereal Company
Postum Cereal Company was an American food manufacturer best known as the predecessor to General Foods and for producing popular breakfast cereals and the Postum coffee substitute.
-
C.
Quaker Oats
Quaker Oats is a well-known American food brand specializing in oatmeal and other grain-based products.
-
D.
General Mills
General Mills is a major American multinational food company known for producing popular brands of cereals, snacks, and packaged foods.
-
E.
Kellogg
Kellogg is a surname most notably associated with American politician and Nobel Peace Prize laureate Frank B. Kellogg, as well as several other prominent figures and institutions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454a158c819093b8e35f5045efb6 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17660c0c88190bed9fa8f6517eec4 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 3:08 p.m.