Triple
T21208995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mars, Incorporated |
E522669
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object | Skittles |
—
|
NE NERFINISHED |
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: Skittles | Statement: [Mars, Incorporated, hasBrand, Skittles]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Skittles Context triple: [Mars, Incorporated, hasBrand, Skittles]
-
A.
Skittles
chosen
Skittles is a popular bite-sized, fruit-flavored candy known for its colorful sugar shells and the slogan "Taste the Rainbow."
-
B.
Froot Loops
Froot Loops is a brightly colored, fruit-flavored breakfast cereal featuring ring-shaped pieces and the toucan mascot Toucan Sam.
-
C.
M&M's
M&M's are colorful button-shaped chocolate candies with a hard sugar shell, famous for their “melts in your mouth, not in your hand” slogan and wide variety of flavors.
-
D.
Smarties
Smarties are colorful sugar-coated chocolate confectionery pieces popular as a candy treat, particularly in Europe and Canada.
-
E.
Gobstoppers
Gobstoppers are colorful, multi-layered hard candies that gradually change flavor and color as they dissolve in the mouth.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b5112d8881909510b2dcdc93106d |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e73436eb4c819082e05caf1ba52672 |
completed | April 21, 2026, 8:24 a.m. |
Created at: April 16, 2026, 3:26 p.m.