Triple
T25074502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shopska salad |
E628009
|
entity |
| Predicate | typicalServingTime |
P181624
|
FINISHED |
| Object | summer |
—
|
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: summer | Statement: [Shopska salad, typicalServingTime, summer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalServingTime Context triple: [Shopska salad, typicalServingTime, summer]
-
A.
typicalCookingTime
Indicates the usual duration required to cook something under standard or commonly accepted conditions.
-
B.
servedTimeFor
Indicates that one entity has completed or spent a specified duration of time serving a sentence, obligation, or term on behalf of another entity or for a particular case or offense.
-
C.
preparationTimeContribution
Indicates how much a given factor, step, or participant adds to the total time required for preparation.
-
D.
servedTimeAt
Indicates the specific time period during which an entity was served or received service at a particular place or context.
-
E.
servingStyle
Indicates how something (typically food or drink) is presented or offered for consumption or use.
- 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_69e2ff2d71dc8190b4758e57d643cbe4 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
| PDg | Predicate description generation | batch_69f7805c25dc8190b9977c561ba15975 |
completed | May 3, 2026, 5:05 p.m. |
Created at: April 18, 2026, 6:20 a.m.