Triple
T14293971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minnetonka |
E354389
|
entity |
| Predicate | hasMajorEmployer |
P588
|
FINISHED |
| Object | Cargill |
E825592
|
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: Cargill | Statement: [Minnetonka, hasMajorEmployer, Cargill]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cargill Context triple: [Minnetonka, hasMajorEmployer, Cargill]
-
A.
Cargill
chosen
Cargill is a large American privately held global food and agribusiness company involved in commodities trading, food production, and agricultural services.
-
B.
Tyson Foods
Tyson Foods is a major American multinational food company best known as one of the world’s largest processors and marketers of chicken, beef, and pork products.
-
C.
Simplot Foods
Simplot Foods is a major American agribusiness and food processing company best known for producing frozen potato products and other processed foods for retail and foodservice markets.
-
D.
Archer Daniels Midland
Archer Daniels Midland is a large American multinational food processing and commodities trading corporation.
-
E.
Hormel Foods Corporation
Hormel Foods Corporation is a major American food company best known for producing branded meat and packaged food products such as SPAM.
- 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de7179368081908117a9ccfbf94fd4 |
completed | April 14, 2026, 4:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3d2281d481909714f8d8cfe71514 |
completed | May 8, 2026, 1:32 a.m. |
Created at: April 10, 2026, 1:11 a.m.