Triple
T2538744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wiener Schnitzel |
E56331
|
entity |
| Predicate | typicalFatUsed |
P40978
|
FINISHED |
| Object | clarified butter |
—
|
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: clarified butter | Statement: [Wiener Schnitzel, typicalFatUsed, clarified butter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalFatUsed Context triple: [Wiener Schnitzel, typicalFatUsed, clarified butter]
-
A.
typicalFuel
Indicates the kind of fuel that is normally or most commonly used by an entity (such as a device, vehicle, or system).
-
B.
metabolismType
Indicates the kind of metabolic process or pathway an entity uses to obtain and transform energy or nutrients.
-
C.
typicalBodyType
Indicates that one entity is the usual or characteristic body type associated with another entity.
-
D.
typicalConsumptionAge
Indicates the age at which something is most commonly or normally consumed.
-
E.
typeOfFasting
Indicates the specific kind or category of fasting practice associated with an entity.
- 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_69ab4a49b6508190bc467fbef4bac334 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd64a2194819097c66cbeb37fe859 |
completed | March 7, 2026, 7:39 a.m. |
| PD | Predicate disambiguation | batch_69abd0c4a5dc819097812db50443420a |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd648487881908ce8ca22def77294 |
completed | March 7, 2026, 7:39 a.m. |
Created at: March 6, 2026, 9:47 p.m.