Triple
T9593693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1855 Bordeaux classification |
E231478
|
entity |
| Predicate | currentPremierCruCount |
P88917
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [1855 Bordeaux classification, currentPremierCruCount, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: currentPremierCruCount Context triple: [1855 Bordeaux classification, currentPremierCruCount, 5]
-
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.
hasPremier
Indicates that an entity has a specific individual serving as its premier (head of government).
-
E.
hasLargestWinegrowingCommune
Indicates that one entity possesses or contains the largest winegrowing commune in comparison to other relevant entities.
- 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.