Triple
T5607471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maggi |
E147267
|
entity |
| Predicate | notableProduct |
P1448
|
FINISHED |
| Object | Maggi seasoning sauce |
E147267
|
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: Maggi seasoning sauce | Statement: [Maggi, notableProduct, Maggi seasoning sauce]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maggi seasoning sauce Context triple: [Maggi, notableProduct, Maggi seasoning sauce]
-
A.
Maggi
chosen
Maggi is a popular global food brand best known for its instant noodles, seasonings, and convenience products.
-
B.
Prego
Prego is a popular American brand of pasta sauces known for its thick, tomato-based varieties and wide range of flavors.
-
C.
Saveur
Saveur is a culinary magazine known for its in-depth exploration of global cuisines, food culture, and travel.
-
D.
Congosto
Congosto is a small municipality in the province of León, Spain, historically noted as the birthplace of the explorer Álvaro de Mendaña de Neira.
-
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_69c0090500f881908374285baf0ac46f |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020fd1b2c81908da154f7e11b90d8 |
completed | March 22, 2026, 5:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c02878aad8819082d2c8f038b79bc7 |
completed | March 22, 2026, 5:35 p.m. |
Created at: March 22, 2026, 3:39 p.m.