Triple
T22504047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saatchi & Saatchi |
E556343
|
entity |
| Predicate | hasClient |
P734
|
FINISHED |
| Object | General Mills |
—
|
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: General Mills | Statement: [Saatchi & Saatchi, hasClient, General Mills]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: General Mills Context triple: [Saatchi & Saatchi, hasClient, General Mills]
-
A.
General Mills
chosen
General Mills is a major American multinational food company known for producing popular brands of cereals, snacks, and packaged foods.
-
B.
Kellogg Company
Kellogg Company is a major American multinational food manufacturing company best known for its breakfast cereals and convenience foods.
-
C.
Kraft Heinz
Kraft Heinz is a major American multinational food and beverage company known for its wide portfolio of iconic packaged brands.
-
D.
Pillsbury Company
Pillsbury Company is a major American food company best known for its packaged baking products, refrigerated doughs, and iconic Doughboy mascot.
-
E.
Kraft Foods
Kraft Foods is a major American food and beverage company known for producing a wide range of packaged grocery products and iconic brands such as Kraft cheese and Oscar Mayer.
- 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_69e11e555edc81909ca803587dafd747 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15d5ac5808190a66f9111c350f4dc |
completed | April 29, 2026, 1:22 a.m. |
Created at: April 16, 2026, 8:50 p.m.