Triple
T5607288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OTC:NSRGY |
E147263
|
entity |
| Predicate | issuerBrandPortfolioIncludes |
P64617
|
FINISHED |
| Object | Maggi |
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 | Statement: [OTC:NSRGY, issuerBrandPortfolioIncludes, Maggi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maggi Context triple: [OTC:NSRGY, issuerBrandPortfolioIncludes, Maggi]
-
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.
Kraft
Kraft is a prominent American surname most widely associated with billionaire businessman and New England Patriots owner Robert Kraft.
-
D.
Heinz Boxes
Heinz Boxes is an artwork by Andy Warhol that, like his Brillo Boxes, consists of painted wooden replicas of commercial Heinz packaging, exploring themes of consumerism and mass production in art.
-
E.
Knorr
Knorr is a global food brand known for its soups, seasonings, bouillon, and ready-made meal products.
- 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_69c021d8d600819097df4e265e262d90 |
completed | March 22, 2026, 5:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04d4465388190b28f47f11e133b6a |
completed | March 22, 2026, 8:12 p.m. |
Created at: March 22, 2026, 3:39 p.m.