Triple
T12452209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knorr |
E297557
|
entity |
| Predicate | notableProduct |
P1448
|
FINISHED |
| Object | Knorr Aromat seasoning |
E297557
|
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: Knorr Aromat seasoning | Statement: [Knorr, notableProduct, Knorr Aromat seasoning]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Knorr Aromat seasoning Context triple: [Knorr, notableProduct, Knorr Aromat seasoning]
-
A.
Knorr
chosen
Knorr is a global food brand known for its soups, seasonings, bouillon, and ready-made meal products.
-
B.
Maggi
Maggi is a popular global food brand best known for its instant noodles, seasonings, and convenience products.
-
C.
Dr. Oetker
Dr. Oetker is a German multinational food company best known for its baking products, desserts, frozen pizzas, and other convenience foods.
-
D.
Heinz
Heinz is a historic American food processing company best known for its ketchup and other condiments.
-
E.
Heinz
Heinz is the German given name of Henry Alfred Kissinger, the influential American diplomat and former U.S. Secretary of State.
- 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_69d6ada166c48190b902972cd2408fa3 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d9fa5f0819080ca9f6efa212c59 |
completed | April 10, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63f16e87c8190b7e9f61561ae865a |
completed | May 2, 2026, 6:14 p.m. |
Created at: April 8, 2026, 9:56 p.m.