Triple
T24893615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montlouis-sur-Loire AOC |
E623072
|
entity |
| Predicate | sparklingWineSweetnessRange |
P157450
|
FINISHED |
| Object | from brut to demi-sec |
—
|
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: from brut to demi-sec | Statement: [Montlouis-sur-Loire AOC, sparklingWineSweetnessRange, from brut to demi-sec]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sparklingWineSweetnessRange Context triple: [Montlouis-sur-Loire AOC, sparklingWineSweetnessRange, from brut to demi-sec]
-
A.
sparklingWineAllowed
Indicates that the use, serving, or presence of sparkling wine is permitted in the given context or under specified conditions.
-
B.
sweetWineSuitability
Indicates the degree to which something is appropriate or recommended for pairing with or serving as a sweet wine.
-
C.
wineAcidityType
Indicates the type or category of acidity associated with a given wine.
-
D.
hasSherrySweetness
Indicates that one entity possesses or exhibits the sweetness characteristic associated with sherry.
-
E.
sweetWinePermitted
Indicates that the consumption or use of sweet wine is allowed under the specified conditions or rules.
- F. None of above. chosen
Provenance (4 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_69e2fac597708190a922bf39a49ec70a |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f43043512481909501a3979cac9947 |
completed | May 1, 2026, 4:46 a.m. |
| PD | Predicate disambiguation | batch_69f420fd375c81908ea4a4e60b76ee8f |
completed | May 1, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f4303fad6c8190844f069164f0904d |
completed | May 1, 2026, 4:46 a.m. |
Created at: April 18, 2026, 5:26 a.m.