Triple
T34257426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mom’s Best Cereals |
E878929
|
entity |
| Predicate | productUsage |
P2529
|
FINISHED |
| Object | breakfast |
—
|
LITERAL 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: breakfast | Statement: [Mom’s Best Cereals, productUsage, breakfast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: productUsage Context triple: [Mom’s Best Cereals, productUsage, breakfast]
-
A.
productsUsedIn
Indicates that certain products are utilized or applied within a particular process, context, or entity.
-
B.
usesProduct
Indicates that one entity makes use of, applies, or employs a particular product.
-
C.
usageType
chosen
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
D.
usedForProduct
Indicates that one entity serves as a tool, component, or means specifically employed in the creation, operation, or delivery of another entity considered as a product.
-
E.
platformUsage
Indicates how an entity uses, engages with, or relies on a particular platform for its activities or services.
- F. None of above.
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_69f349b421cc8190b4b4655e1d612548 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fe8ddf70e48190a917eb9e8f7b6966 |
completed | May 9, 2026, 1:29 a.m. |
| PD | Predicate disambiguation | batch_69fe87ef94dc81909bb00ec8d6de9bcd |
completed | May 9, 2026, 1:03 a.m. |
Created at: May 1, 2026, 1:56 a.m.