Triple
T3853604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fronton AOC |
E85356
|
entity |
| Predicate | typicalRoséCharacter |
P51955
|
FINISHED |
| Object | fruity |
—
|
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: fruity | Statement: [Fronton AOC, typicalRoséCharacter, fruity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalRoséCharacter Context triple: [Fronton AOC, typicalRoséCharacter, fruity]
-
A.
typicalRedProfile
Indicates that an entity exhibits a characteristic or standard pattern commonly associated with the color red.
-
B.
typicalRole
Indicates that one entity serves as the usual, characteristic, or commonly expected role or function of another entity.
-
C.
typicalBlendPartner
Indicates that two entities are commonly or characteristically combined or mixed together as standard or usual partners.
-
D.
typicalProfile
Indicates that an entity represents the standard or most representative profile or pattern for another entity.
-
E.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
- 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_69aed936de1c81908f91bed80f70abb2 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec0438308190865ff74bee5a1cf2 |
completed | March 9, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69aee750377c8190af70c79768c0edd8 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aee8d9b328819080158be59e5bcc97 |
completed | March 9, 2026, 3:35 p.m. |
Created at: March 9, 2026, 3:19 p.m.