Triple
T2706578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hellmann's |
E59354
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Hellmann's Vegan Mayo |
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 Vegan Mayo | Statement: [Hellmann's, hasVariant, Hellmann's Vegan Mayo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hellmann's Vegan Mayo Context triple: [Hellmann's, hasVariant, Hellmann's Vegan Mayo]
-
A.
Hellmann
chosen
Hellmann is a common surname and brand name, most notably associated with the international mayonnaise and condiments brand.
-
B.
Colman’s Mustard
Colman’s Mustard is a historic British mustard brand, famed for its distinctive hot English mustard powder and long-standing production heritage.
-
C.
Mustardinha
Mustardinha is a neighborhood located in the city of Recife, in northeastern Brazil.
-
D.
baba ghanoush
Baba ghanoush is a Middle Eastern dip made from roasted eggplant blended with tahini, lemon juice, garlic, and seasonings.
-
E.
Jell-O
Jell-O is a popular brand of flavored gelatin desserts and related products that became a staple of American cuisine and advertising in the 20th century.
- 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_69ab4ac66bc88190b9e4afa5fc843f72 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda725f24819090e8d936b3d2d5bc |
completed | March 7, 2026, 7:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afaf7c22a4819096ff9effe9e0d77d |
completed | March 10, 2026, 5:43 a.m. |
Created at: March 6, 2026, 9:55 p.m.