Triple
T15146808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kicking Horse Coffee |
E361828
|
entity |
| Predicate | roastProfile |
P117501
|
FINISHED |
| Object | light roasts |
—
|
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: light roasts | Statement: [Kicking Horse Coffee, roastProfile, light roasts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roastProfile Context triple: [Kicking Horse Coffee, roastProfile, light roasts]
-
A.
typicalRoastUse
Indicates that something is commonly or characteristically used for roasting.
-
B.
isCookedBy
Indicates that something has been prepared or made ready for eating through cooking by a particular agent.
-
C.
chef
Indicates that one entity serves as the cook or culinary professional responsible for preparing food for another entity or context.
-
D.
servedHot
Indicates that something is provided or presented in a heated or warm state, suitable for immediate consumption.
-
E.
seasoningStyle
Indicates the characteristic way in which an item is flavored or seasoned, such as the method, intensity, or cultural style of its seasoning.
- F. None of above. chosen
Provenance (4 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_69d85a0759908190b8a051d2e2a1cbe6 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005c825a481909d00098b0e743365 |
completed | April 15, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69deb9713fe881909dec2fd3f6c84b39 |
completed | April 14, 2026, 10:02 p.m. |
| PDg | Predicate description generation | batch_69dec71e8dcc81908badc834b6ccf273 |
completed | April 14, 2026, 11 p.m. |
Created at: April 10, 2026, 3:07 a.m.