Triple
T9593692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1855 Bordeaux classification |
E231478
|
entity |
| Predicate | originalPremierCruCount |
P88917
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [1855 Bordeaux classification, originalPremierCruCount, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalPremierCruCount Context triple: [1855 Bordeaux classification, originalPremierCruCount, 4]
-
A.
numberOfPremierCruClimats
chosen
Indicates the count of premier cru climats associated with a given entity.
-
B.
notablePremierCru
Indicates that a subject is recognized as a distinguished or especially noteworthy Premier Cru within its classification.
-
C.
hasGrandCru
Indicates that an entity possesses, is associated with, or includes a wine classified as Grand Cru.
-
D.
positionInCôteDeBeaune
Indicates that something is located within or belongs to the Côte de Beaune subregion.
-
E.
primaryGrapeVariety
Indicates that one entity is the main or predominant grape variety used in producing the other entity (typically a wine or wine-based product).
- 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_69ca8482884481908eccdfdf64d6fbf7 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9a134b0c81908a568e5d2ecfbb92 |
completed | April 1, 2026, 10:20 p.m. |
| PD | Predicate disambiguation | batch_69ccd5a359788190b24f82399489f7fe |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:07 p.m.