Triple
T23366323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Touraine-Noble Joué AOC |
E593332
|
entity |
| Predicate | typicalPalate |
P69349
|
FINISHED |
| Object | light-bodied |
—
|
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: light-bodied | Statement: [Touraine-Noble Joué AOC, typicalPalate, light-bodied]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPalate Context triple: [Touraine-Noble Joué AOC, typicalPalate, light-bodied]
-
A.
leafTaste
Indicates that one entity has a particular taste or flavor associated with its leaves.
-
B.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
C.
hasTastingProfile
chosen
Indicates that an entity possesses a specific flavor or sensory profile, typically describing its characteristic tastes and aromas.
-
D.
typicalFoodPairing
Indicates that one food item is commonly served, consumed, or matched together with another as a customary or complementary pairing.
-
E.
cuisine
Indicates the type or style of food traditionally associated with or served by an entity (such as a restaurant or region).
- 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_69e25d2593c88190bcdf4a716a94ccb2 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a0ac7494819082e98ac5632eba28 |
completed | April 29, 2026, 6:09 a.m. |
| PD | Predicate disambiguation | batch_69f061c7aaa48190a58ce93f87155ffc |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:31 p.m.