Triple
T17076529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sprite Ice |
E414360
|
entity |
| Predicate | sensoryAttribute |
P35696
|
FINISHED |
| Object | cooling mouthfeel |
—
|
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: cooling mouthfeel | Statement: [Sprite Ice, sensoryAttribute, cooling mouthfeel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sensoryAttribute Context triple: [Sprite Ice, sensoryAttribute, cooling mouthfeel]
-
A.
perceivedAttribute
Indicates that one entity recognizes, interprets, or assigns a particular attribute or quality to another entity.
-
B.
spanCharacteristic
Indicates that one entity has a particular measurable or descriptive property that characterizes the extent, duration, or range of another entity or phenomenon.
-
C.
fruitCharacteristic
Indicates that a specified characteristic or property is attributed to a particular fruit.
-
D.
valueCharacteristic
Indicates that one entity serves as a value or specific quantitative/qualitative measure that characterizes or describes another entity.
-
E.
providesSensoryEffects
chosen
Indicates that one entity causes or contributes to sensory experiences or perceptions in another entity.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbc559388190b685504cca6ed62b |
completed | April 18, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69e35d642f74819098c014135e249b27 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:34 a.m.