Triple
T23635425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cloudy Bay |
E583728
|
entity |
| Predicate | wineRegionClimate |
P40401
|
FINISHED |
| Object | cool maritime climate |
—
|
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: cool maritime climate | Statement: [Cloudy Bay, wineRegionClimate, cool maritime climate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wineRegionClimate Context triple: [Cloudy Bay, wineRegionClimate, cool maritime climate]
-
A.
viticulturalClimate
chosen
Indicates the type of climate conditions relevant to grape growing and wine production that characterize a given region or area.
-
B.
shareClimateZones
Indicates that two entities are located in regions classified under the same climate zone or zones.
-
C.
wineClassificationRegion
Indicates that a wine is classified according to the geographic region where it is produced or designated.
-
D.
wineRegion
Indicates the geographical region or area where a particular wine is produced or originates.
-
E.
wineRegionCategory
Indicates a classification relationship where a wine region is assigned to a specific category or type of wine-producing area.
- 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_69e248fe1c2c8190ac914d2442ff3d26 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b1ec38f48190832d919391971ddb |
completed | April 29, 2026, 7:23 a.m. |
| PD | Predicate disambiguation | batch_69f118d7903c8190bb590a71771e93af |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:47 p.m.