Triple
T1202696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anderson Valley AVA |
E25817
|
entity |
| Predicate | diurnalRange |
P25527
|
FINISHED |
| Object | large diurnal 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 diurnal temperature variation | Statement: [Anderson Valley AVA, diurnalRange, large diurnal temperature variation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: diurnalRange Context triple: [Anderson Valley AVA, diurnalRange, large diurnal temperature variation]
-
A.
typicalRange
Indicates the usual or expected range of values, conditions, or states within which something normally occurs or applies.
-
B.
surfaceTemperatureRange
Indicates the range between the minimum and maximum surface temperatures observed or allowed for an entity.
-
C.
dayLengthCharacteristic
Indicates a relationship where an entity is characterized or defined by the length or duration of its day.
-
D.
typicalTemperature
Indicates the usual or characteristic temperature associated with an entity under normal conditions.
-
E.
hasTidalRange
Indicates the relationship between a location or body of water and the magnitude of difference between its high and low tide levels.
- F. None of above. chosen
Provenance (4 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_69a4942b30f08190a91c60573e16b5ef |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bdbda0b081909c0147121a945e27 |
completed | March 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5ed2b88190aab992913957e1cf |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bcc82e38819081c3615e1cc7a66f |
completed | March 1, 2026, 10:25 p.m. |
Created at: March 1, 2026, 7:46 p.m.