Triple
T21815062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Picardan |
E538584
|
entity |
| Predicate | typicalUseProportion |
P124051
|
FINISHED |
| Object | small percentage of blend |
—
|
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: small percentage of blend | Statement: [Picardan, typicalUseProportion, small percentage of blend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalUseProportion Context triple: [Picardan, typicalUseProportion, small percentage of blend]
-
A.
typicalUseRatio
chosen
Indicates the proportion or share in which something is commonly or normally used relative to other possible uses or components.
-
B.
hasProportion
Indicates that one entity stands in a specified ratio, fraction, or relative share to another entity or whole.
-
C.
usageAmong
Indicates how frequently or in what manner something is used within a particular group, context, or population.
-
D.
officialProportion
Indicates the proportion or percentage of something as formally defined or reported by an official source or authority.
-
E.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
- 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_69e0c473f0f8819086c9d1b4a143bd67 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f07cc99bbc8190bf074930f361af7d |
completed | April 28, 2026, 9:24 a.m. |
| PD | Predicate disambiguation | batch_69e6be815a108190be81d7c987d0c0d6 |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:54 p.m.