Triple
T1998499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Cru (Burgundy classification) |
E43410
|
entity |
| Predicate | associatedWithPriceLevel |
P35383
|
FINISHED |
| Object | very high |
—
|
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: very high | Statement: [Grand Cru (Burgundy classification), associatedWithPriceLevel, very high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithPriceLevel Context triple: [Grand Cru (Burgundy classification), associatedWithPriceLevel, very high]
-
A.
associatedWithLowPointPrice
Indicates that something has a connection or correlation with a low point-based price or minimum price level.
-
B.
priceRelationship
Indicates a comparative relationship between the prices of two entities, such as one being higher, lower, or equal to the other.
-
C.
associatedWithRank
Indicates a relationship where an entity is linked to a specific rank, level, or hierarchical position.
-
D.
associatedWithFlag
Indicates a relationship where an entity is linked or connected to a particular flag, such as a national, organizational, or symbolic banner.
-
E.
priceInfluencedBy
Indicates that the price of one entity is affected or determined by another specified factor or entity.
- F. None of above. chosen
Provenance (4 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_69a88715dbbc8190b2299e29e955d997 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb91055d88190a980e7b42e5895d4 |
completed | March 7, 2026, 5:35 a.m. |
| PD | Predicate disambiguation | batch_69abb79c97d48190b3147430ed39faa9 |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb90ec7948190bbfb0329e9e67cca |
completed | March 7, 2026, 5:35 a.m. |
Created at: March 4, 2026, 7:37 p.m.