Triple
T11393313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clos Montmartre vineyard |
E269901
|
entity |
| Predicate | plantedArea |
P63925
|
FINISHED |
| Object | approximately 0.15 hectares of vines |
—
|
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: approximately 0.15 hectares of vines | Statement: [Clos Montmartre vineyard, plantedArea, approximately 0.15 hectares of vines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plantedArea Context triple: [Clos Montmartre vineyard, plantedArea, approximately 0.15 hectares of vines]
-
A.
plantArea
chosen
Indicates the total surface area occupied or covered by a plant or group of plants.
-
B.
plantedIn
Indicates that one entity has been placed or sown into another entity as its growing or containing medium.
-
C.
plantedAt
Indicates that one entity has been planted or placed into the ground or a specific location at or in association with another entity.
-
D.
acquiredLandArea
Indicates the total area of land that has been obtained or taken possession of through an acquisition.
-
E.
coveredArea
Indicates that one entity occupies or extends over a specific spatial region or surface area associated with another entity.
- 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_69d6aacdbc6c8190af6dc3d5f5d22836 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d8001796f48190822526f52e3f0337 |
completed | April 9, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69d7e70b228c8190b87f5101fd683788 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:34 p.m.