Triple
T29591754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moon Mountain District AVA |
E754180
|
entity |
| Predicate | diurnalShift |
P25527
|
FINISHED |
| Object | large day-night temperature variation |
—
|
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: large day-night temperature variation | Statement: [Moon Mountain District AVA, diurnalShift, large day-night temperature variation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: diurnalShift Context triple: [Moon Mountain District AVA, diurnalShift, large day-night temperature variation]
-
A.
isDiurnal
Indicates that an entity is active during the daytime and rests at night.
-
B.
dayNightVariant
Indicates a relationship where one entity is a day-time version and the other is a night-time version of the same underlying thing.
-
C.
diurnalRange
chosen
Indicates the difference between the daily maximum and minimum values of a measured quantity, typically temperature, over a 24-hour period.
-
D.
associatedTimeOfDay
Indicates the specific time of day during which an event, state, or relationship occurs or is most relevant.
-
E.
shiftsWhen
Indicates that one state, condition, or configuration changes to another under specified circumstances or triggers.
- 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_69f0ef836ac88190bd809dc58b5ec907 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f66db3fdb481909b90ad0a24aaa005 |
completed | May 2, 2026, 9:33 p.m. |
| PD | Predicate disambiguation | batch_69f6659d36208190b01412600a4ed57d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 6:14 p.m.