Triple
T4039379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Mountain AVA |
E83905
|
entity |
| Predicate | windInfluence |
P31348
|
FINISHED |
| Object | moderate winds that reduce disease pressure |
—
|
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: moderate winds that reduce disease pressure | Statement: [Red Mountain AVA, windInfluence, moderate winds that reduce disease pressure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: windInfluence Context triple: [Red Mountain AVA, windInfluence, moderate winds that reduce disease pressure]
-
A.
hasClimateInfluence
Indicates that one entity affects or contributes to the climate characteristics or climate-related conditions of another entity.
-
B.
windResource
Indicates the availability, quality, or characteristics of wind at a location as a usable energy resource.
-
C.
windResistance
Indicates the degree to which an entity opposes or reduces the effect of wind acting upon it.
-
D.
influenced
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
E.
typeOfInfluence
chosen
Indicates the specific nature or category of influence that one entity exerts on another.
- 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_69aed92f7cf0819098e0539bdcc3767f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb37e24c81908d6357ab8ba5388d |
completed | March 9, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69aef900386481909d04555a9ec9b0e3 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:37 p.m.