Triple
T2553194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frappuccino blended beverages |
E56672
|
entity |
| Predicate | typicalUseTime |
P6833
|
FINISHED |
| Object | afternoon refreshment |
—
|
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: afternoon refreshment | Statement: [Frappuccino blended beverages, typicalUseTime, afternoon refreshment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalUseTime Context triple: [Frappuccino blended beverages, typicalUseTime, afternoon refreshment]
-
A.
durationOfUse
Indicates the length of time for which something is used or remains in use.
-
B.
typicalDurationDays
Indicates the usual or expected number of days that an associated event, process, or state typically lasts.
-
C.
typicalTimes
chosen
Indicates the usual or characteristic times at which an event, activity, or condition typically occurs.
-
D.
periodOfMajorUse
Indicates the time span during which something was primarily or most intensively used.
-
E.
typicalConsumptionAge
Indicates the age at which something is most commonly or normally consumed.
- 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_69ab4a4bfec081908039988ec4c86e28 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd5a33234819082ad49fa6594b6be |
completed | March 7, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69abd0c8b6f08190a68645db3e8b779a |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:48 p.m.