Triple
T3827481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cahors AOC |
E88724
|
entity |
| Predicate | maximumOtherVarietiesPercentage |
P16308
|
FINISHED |
| Object | 30% |
—
|
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: 30% | Statement: [Cahors AOC, maximumOtherVarietiesPercentage, 30%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumOtherVarietiesPercentage Context triple: [Cahors AOC, maximumOtherVarietiesPercentage, 30%]
-
A.
numberOfPrimaryVarieties
Indicates the count of distinct primary varieties associated with a given entity.
-
B.
hasApproximateNumberOfVarieties
Indicates that an entity is associated with an estimated or non-exact count of different varieties or types.
-
C.
standardVarietyBasedIn
Indicates that a standard or reference variety (such as a language or dialect) is primarily established, recognized, or centered in a particular location or region.
-
D.
varietyOf
Indicates that one entity is a specific type, kind, or variant of another, more general entity.
-
E.
hasProportion
chosen
Indicates that one entity stands in a specified ratio, fraction, or relative share to another entity or whole.
- 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_69aed9538cf881909d9ce8ca4ac7c18c |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeb8459f881908a2c91bb07e381ef |
completed | March 9, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69aee74c2e04819094b94b3c0bac1806 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:17 p.m.