Triple
T24935750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Almond Chocolate |
E623306
|
entity |
| Predicate | coatedWith |
P81140
|
FINISHED |
| Object | smooth chocolate |
—
|
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: smooth chocolate | Statement: [Almond Chocolate, coatedWith, smooth chocolate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coatedWith Context triple: [Almond Chocolate, coatedWith, smooth chocolate]
-
A.
coatingType
chosen
Indicates the type or kind of coating applied to or associated with an entity.
-
B.
isThickenedWith
Indicates that one substance has been made more viscous or dense by adding another substance that serves as a thickening agent.
-
C.
adornedWith
Indicates that one entity is decorated, embellished, or ornamented by another entity.
-
D.
inlaidWith
Indicates that one object has decorative material set into its surface, typically flush with it, using a contrasting substance or pattern.
-
E.
skeletonCoating
Indicates that one entity serves as a coating, covering, or outer layer on the skeleton of another entity.
- 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_69e2fac6b5a48190a1c38857f00915a9 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f423d5a0f48190b4df532471cd37d1 |
completed | May 1, 2026, 3:53 a.m. |
| PD | Predicate disambiguation | batch_69f4210130d08190ae30b7943f7a0bbc |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 5:30 a.m.