Triple
T26775038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Couchey |
E670093
|
entity |
| Predicate | hasVineyardSlope |
P167300
|
FINISHED |
| Object |
Côte de Couchey
Côte de Couchey is a Burgundy vineyard slope in eastern France known for producing appellation-quality wines, particularly from Pinot Noir and Chardonnay grapes.
|
E1745658
|
NE FINISHED |
How this triple was built (3 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: Côte de Couchey | Statement: [Couchey, hasVineyardSlope, Côte de Couchey]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Côte de Couchey Triple: [Couchey, hasVineyardSlope, Côte de Couchey]
Generated description
Côte de Couchey is a Burgundy vineyard slope in eastern France known for producing appellation-quality wines, particularly from Pinot Noir and Chardonnay grapes.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVineyardSlope Context triple: [Couchey, hasVineyardSlope, Côte de Couchey]
-
A.
hasVineyards
Indicates that one entity possesses, contains, or is associated with vineyards used for growing grapevines.
-
B.
hasVineyardType
Indicates the specific type or classification of a vineyard associated with an entity.
-
C.
hasVineyardsNear
Indicates that one entity possesses or is associated with vineyards located in close geographic proximity to another entity.
-
D.
isEstateVineyardFor
Indicates that a vineyard is directly owned, managed, and used to produce wine for a specific winery or estate.
-
E.
neighboringVineyard
Indicates that one vineyard is located adjacent to or very close to another vineyard.
- F. None of above. chosen
Provenance (7 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_69eeb31c925881909b597f6e40056d28 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f66a6468ec8190a43ed6cd8c797f42 |
completed | May 2, 2026, 9:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a12132e1f7c8190b55d411f437e7247 |
completed | May 23, 2026, 8:50 p.m. |
| NEDg | Description generation | batch_6a121416401481908c0fa6e1c2e9e317 |
completed | May 23, 2026, 8:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a1217e349a08190a986e6ce56f5b82d |
completed | May 23, 2026, 9:10 p.m. |
| PD | Predicate disambiguation | batch_69f66598d6008190a7ca8ff80399fd34 |
completed | May 2, 2026, 8:59 p.m. |
| PDg | Predicate description generation | batch_69f6691da93081909deaf680614fc900 |
completed | May 2, 2026, 9:14 p.m. |
Created at: April 27, 2026, 4:04 a.m.