Triple
T23760182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sweet and Sour Carp |
E587227
|
entity |
| Predicate | typicalSauce |
P51950
|
FINISHED |
| Object | sweet and sour sauce |
—
|
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: sweet and sour sauce | Statement: [Sweet and Sour Carp, typicalSauce, sweet and sour sauce]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSauce Context triple: [Sweet and Sour Carp, typicalSauce, sweet and sour sauce]
-
A.
sauceType
chosen
Indicates the specific kind or category of sauce associated with an item or dish.
-
B.
typicalSauceConsistency
Indicates that something has the usual or characteristic thickness or texture expected of a sauce.
-
C.
isTypicallyGarnishedWith
Indicates that one item is commonly used as a garnish or decorative finishing element for another.
-
D.
typicalSpices
Indicates that certain spices are commonly or characteristically used in association with a particular dish, cuisine, or ingredient.
-
E.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
- 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_69e2490b8ac48190a6b35f1d5500486b |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1bdb1d6348190afb3f0fbea1b9ca3 |
completed | April 29, 2026, 8:13 a.m. |
| PD | Predicate disambiguation | batch_69f155f79e34819080f9ddb972b34deb |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:14 p.m.