Triple
T22441350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sichuan hot pot |
E554760
|
entity |
| Predicate | heatLevel |
P34515
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Sichuan hot pot, heatLevel, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: heatLevel Context triple: [Sichuan hot pot, heatLevel, high]
-
A.
hasSpiciness
chosen
Indicates that one entity possesses a certain level or quality of spiciness in relation to another entity or a defined scale.
-
B.
hasTasteIntensity
Indicates the degree or strength of taste associated with something.
-
C.
calorieLevel
Indicates the relationship between an entity and the amount of calories it contains or provides, typically categorized by intensity or range (e.g., low, medium, high).
-
D.
typicalSweetnessLevel
Indicates the usual or characteristic degree of sweetness associated with something.
-
E.
hasBitternessLevel
Indicates that an entity is associated with a specific degree or intensity of bitterness.
- 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_69e11e5010e48190ae1e9c9db9697637 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ae1f82881908a611f134eb03f3d |
completed | April 29, 2026, 1:12 a.m. |
| PD | Predicate disambiguation | batch_69e898a327948190beee5e168006a0a7 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:47 p.m.