Triple
T12454992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penola |
E297633
|
entity |
| Predicate | wineRegionFeature |
P9793
|
FINISHED |
| Object | terra rossa soils in nearby Coonawarra |
—
|
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: terra rossa soils in nearby Coonawarra | Statement: [Penola, wineRegionFeature, terra rossa soils in nearby Coonawarra]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wineRegionFeature Context triple: [Penola, wineRegionFeature, terra rossa soils in nearby Coonawarra]
-
A.
wineRegionCategory
Indicates a classification relationship where a wine region is assigned to a specific category or type of wine-producing area.
-
B.
wineRegionSpecialization
Indicates a relationship where a wine-producing region is characterized by or particularly known for specializing in a specific type or style of wine.
-
C.
wineCharacteristic
Indicates a descriptive property or quality attributed to a wine, such as its flavor, aroma, color, or style.
-
D.
wineRegion
Indicates the geographical region or area where a particular wine is produced or originates.
-
E.
viticulturalCharacteristic
chosen
Indicates a relationship where a specific trait, quality, or property is attributed to viticulture or grape-growing practices.
- 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_69d6ada166c48190b902972cd2408fa3 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95151e7348190a1d4953a8b416a13 |
completed | April 10, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69d94d3c27a08190a0237200203e476d |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.