Triple
T6653809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbera d’Asti |
E150889
|
entity |
| Predicate | acidityCharacter |
P56868
|
FINISHED |
| Object | bright acidity |
—
|
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: bright acidity | Statement: [Barbera d’Asti, acidityCharacter, bright acidity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: acidityCharacter Context triple: [Barbera d’Asti, acidityCharacter, bright acidity]
-
A.
acidityLevel
Indicates the degree or intensity of acidity associated with an entity, typically measured by pH or a comparable scale.
-
B.
wineAcidityType
chosen
Indicates the type or category of acidity associated with a given wine.
-
C.
character3
Indicates a tertiary or additional character role associated with an entity, typically the third distinct character linked within a given context or work.
-
D.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
E.
typeOfCharacter
Indicates that one entity is a specific kind or category of character in relation to 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_69c687f2c9508190a60b9aad31d3f358 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6cc9c6cb0819084fec8e0beb430de |
completed | March 27, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69c6ad071b0081909b96dd4b93414bd1 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:01 p.m.