Triple
T8623133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | mchadi |
E204215
|
entity |
| Predicate | oilUsage |
P84497
|
FINISHED |
| Object | often fried in vegetable oil |
—
|
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: often fried in vegetable oil | Statement: [mchadi, oilUsage, often fried in vegetable oil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oilUsage Context triple: [mchadi, oilUsage, often fried in vegetable oil]
-
A.
fuelConsumption
Indicates the amount of fuel used by an entity (such as a vehicle or device) over a specified distance, time, or operation.
-
B.
fuelEfficiency
Indicates how effectively an entity uses fuel to perform a given amount of work or travel a certain distance.
-
C.
energyUse
Indicates the amount or rate at which an entity consumes energy to perform its functions or activities.
-
D.
typeOfGasUsed
Indicates the specific kind of gas that is utilized in relation to an entity or process.
-
E.
energyUtilization
Indicates how effectively an entity uses available energy to perform work or sustain its functions.
- 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_69ca834a4ea0819094970dceb9e389f3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5730309081909a9a0256c9bf5f8f |
completed | March 31, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69cc455906f8819082edd79cb4a1cf28 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc572d99bc819097f36b140c2ee1ce |
completed | March 31, 2026, 11:22 p.m. |
Created at: March 30, 2026, 6:26 p.m.