Triple
T2491293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sauternes |
E52047
|
entity |
| Predicate | sweetnessLevel |
P2068
|
FINISHED |
| Object | lusciously sweet |
—
|
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: lusciously sweet | Statement: [Sauternes, sweetnessLevel, lusciously sweet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sweetnessLevel Context triple: [Sauternes, sweetnessLevel, lusciously sweet]
-
A.
isSweeterThan
Indicates that one entity has a higher level of sweetness in taste compared to another entity.
-
B.
hasBitternessLevel
Indicates that an entity is associated with a specific degree or intensity of bitterness.
-
C.
typicalFlavor
chosen
Indicates that something characteristically has or is associated with a particular flavor.
-
D.
hasSpiciness
Indicates that one entity possesses a certain level or quality of spiciness in relation to another entity or a defined scale.
-
E.
traditionalSweet
Indicates that something is a sweet food or dessert prepared according to long-established customs or cultural traditions.
- 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_69ab4955111c8190835bf619adec21ff |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd1914ca48190ab0a6cc5f1bd2f56 |
completed | March 7, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69abd0b980b481908d4932bcea4a6167 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:45 p.m.