Triple
T16223378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bled cream cake |
E393784
|
entity |
| Predicate | typicalPortion |
P3664
|
FINISHED |
| Object | single square slice |
—
|
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: single square slice | Statement: [Bled cream cake, typicalPortion, single square slice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPortion Context triple: [Bled cream cake, typicalPortion, single square slice]
-
A.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
B.
typicalSplit
Indicates that something is divided into parts or portions in the usual or most common way.
-
C.
typicalUnitSize
chosen
Indicates the standard or most common size or quantity in which something is typically measured, packaged, or used.
-
D.
typicalOrder
Indicates the usual or most common sequence or arrangement in which related elements, events, or components occur.
-
E.
typicalIngredientRatio
Indicates the usual proportional relationship between different ingredients used together in a preparation or mixture.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e23d23e63881908806920d878f2adb |
completed | April 17, 2026, 2:01 p.m. |
| PD | Predicate disambiguation | batch_69e219e94a448190b73a4e6aa374eb4a |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:03 a.m.