Triple
T22919012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mondelez International |
E568804
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object | Dairy Milk |
—
|
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: Dairy Milk | Statement: [Mondelez International, brand, Dairy Milk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dairy Milk Context triple: [Mondelez International, brand, Dairy Milk]
-
A.
Cadbury Dairy Milk
chosen
Cadbury Dairy Milk is a popular British milk chocolate bar brand known for its creamy texture and wide variety of flavors.
-
B.
Milk
Milk is a nutrient-rich white liquid produced by the mammary glands of mammals and widely consumed as a staple food and beverage by humans.
-
C.
Milk
Milk is a 2008 biographical film about gay rights activist and politician Harvey Milk, directed by Gus Van Sant and starring Sean Penn.
-
D.
Mishti Doi
Mishti Doi is a traditional Bengali dessert of caramelized sweetened yogurt, cherished across India for its rich, creamy taste and distinctive earthen-pot preparation.
-
E.
Beer Milka
Beer Milka is a small agricultural community (moshav) in Israel’s Negev desert, near the Egyptian border.
- 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_69e2458d90c88190a58cead4e781ca6a |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f180d316188190901d9356c07110e3 |
completed | April 29, 2026, 3:53 a.m. |
Created at: April 17, 2026, 3:42 p.m.