Triple
T34274889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cidre Pays d’Auge |
E879423
|
entity |
| Predicate | sugarContentRange |
P112699
|
FINISHED |
| Object | varies from dry to sweet |
—
|
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: varies from dry to sweet | Statement: [Cidre Pays d’Auge, sugarContentRange, varies from dry to sweet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sugarContentRange Context triple: [Cidre Pays d’Auge, sugarContentRange, varies from dry to sweet]
-
A.
hasSugarContent
Indicates that one entity possesses or contains a specified amount or level of sugar.
-
B.
sugarContentCategory
chosen
Indicates the classification of something based on how much sugar it contains (e.g., low, medium, or high sugar content).
-
C.
isSugarFree
Indicates that something does not contain sugar or has been formulated without added sugar.
-
D.
hasSugarFreeVariant
Indicates that an item has a corresponding version or option that is formulated without sugar.
-
E.
sweetenerType
Indicates the specific kind or category of sweetener associated with or used in relation to an 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_69f349b5f6648190b9420d94a4cd16e0 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71362f1448190985a80ce7af475cb |
completed | May 3, 2026, 9:20 a.m. |
| PD | Predicate disambiguation | batch_69f7127884388190884f23d181a65d19 |
completed | May 3, 2026, 9:16 a.m. |
Created at: May 1, 2026, 1:56 a.m.