Triple
T17254746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prunelart |
E418850
|
entity |
| Predicate | typicalAlcoholLevelInWine |
P89196
|
FINISHED |
| Object | moderate to high |
—
|
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: moderate to high | Statement: [Prunelart, typicalAlcoholLevelInWine, moderate to high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAlcoholLevelInWine Context triple: [Prunelart, typicalAlcoholLevelInWine, moderate to high]
-
A.
alcoholLevel
Indicates the measured concentration or amount of alcohol present in an entity (such as a person, substance, or environment).
-
B.
alcoholRange
Indicates the range or interval of alcohol content associated with an entity (e.g., minimum and maximum alcohol level).
-
C.
typicalAlcoholRangeRed
chosen
Indicates that the subject red wine typically falls within a specified range of alcohol content.
-
D.
regulatesAlcoholLevel
Indicates a relationship where one entity controls, adjusts, or maintains the alcohol level of another entity or system.
-
E.
minimumAlcohol
Indicates that there is a specified minimum amount or concentration of alcohol required or present in the described context.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e6c362c819088965c6e05f33faf |
completed | April 19, 2026, 1:22 a.m. |
| PD | Predicate disambiguation | batch_69e3832a284481908a8a3da7ac91de5a |
completed | April 18, 2026, 1:12 p.m. |
Created at: April 10, 2026, 5:39 a.m.