Triple
T32780270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camaralet de Lasseube |
E838334
|
entity |
| Predicate | typicalPalateCharacteristic |
P69349
|
FINISHED |
| Object | high aromatics |
—
|
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: high aromatics | Statement: [Camaralet de Lasseube, typicalPalateCharacteristic, high aromatics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPalateCharacteristic Context triple: [Camaralet de Lasseube, typicalPalateCharacteristic, high aromatics]
-
A.
hasTastingProfile
chosen
Indicates that an entity possesses a specific flavor or sensory profile, typically describing its characteristic tastes and aromas.
-
B.
tasteInfluence
Indicates how one entity’s characteristics, actions, or presence affect or shape another entity’s preferences, likes, or aesthetic tastes.
-
C.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
D.
hasTasteIntensity
Indicates the degree or strength of taste associated with something.
-
E.
typicalTongue
Indicates that the subject has a tongue that is typical or characteristic for its kind or category.
- 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_69f3493b83f48190be335cd42465cecf |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:14 a.m.