Triple
T26553690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malmsey |
E671745
|
entity |
| Predicate | wineStylePositionInMadeiraSweetnessScale |
P2082
|
FINISHED |
| Object | sweetest style |
—
|
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: sweetest style | Statement: [Malmsey, wineStylePositionInMadeiraSweetnessScale, sweetest style]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wineStylePositionInMadeiraSweetnessScale Context triple: [Malmsey, wineStylePositionInMadeiraSweetnessScale, sweetest style]
-
A.
sparklingWineSweetnessRange
Indicates the range of sweetness levels that a sparkling wine can have or is classified within.
-
B.
hasSherrySweetness
Indicates that one entity possesses or exhibits the sweetness characteristic associated with sherry.
-
C.
wineDenomination
Indicates that a wine is classified under a specific official denomination or appellation.
-
D.
wineStyle
chosen
Indicates the stylistic category or type of wine (such as its production style, sweetness, body, or other defining characteristics) associated with an entity.
-
E.
sweetWineSuitability
Indicates the degree to which something is appropriate or recommended for pairing with or serving as a sweet wine.
- 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_69eeb32163f08190af5f81282738e27a |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f6146436408190bec22ccca6458ca8 |
completed | May 2, 2026, 3:12 p.m. |
| PD | Predicate disambiguation | batch_69f602d7b1b0819095ddd3b5169f8ce2 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 27, 2026, 1:48 a.m.