Triple
T2784811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unilever |
E61784
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object | Hellmann's |
E59354
|
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: Hellmann's | Statement: [Unilever, hasBrand, Hellmann's]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hellmann's Context triple: [Unilever, hasBrand, Hellmann's]
-
A.
Hellmann
chosen
Hellmann is a common surname and brand name, most notably associated with the international mayonnaise and condiments brand.
-
B.
Heinz
Heinz is the German given name of Henry Alfred Kissinger, the influential American diplomat and former U.S. Secretary of State.
-
C.
Pepperidge Farm
Pepperidge Farm is an American food company best known for its cookies, crackers, and baked goods such as Milano cookies and Goldfish crackers.
-
D.
Kraft
Kraft is a prominent American surname most widely associated with billionaire businessman and New England Patriots owner Robert Kraft.
-
E.
Oscar Mayer
Oscar Mayer was a German-American entrepreneur best known for founding the Oscar Mayer meat and cold cut company, a major U.S. food brand.
- 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_69ab4b7e43c48190997b8fc8fb1663ab |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddaf223c8190959bb0b336e5b7c0 |
completed | March 7, 2026, 8:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc0629e8c81909b55d9838e681ba2 |
completed | March 10, 2026, 6:55 a.m. |
Created at: March 6, 2026, 9:57 p.m.