Triple
T8297017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clayton, California |
E194244
|
entity |
| Predicate | winterWeather |
P10789
|
FINISHED |
| Object | mild wet winters |
—
|
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: mild wet winters | Statement: [Clayton, California, winterWeather, mild wet winters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winterWeather Context triple: [Clayton, California, winterWeather, mild wet winters]
-
A.
winterCharacteristic
chosen
Indicates a characteristic, feature, or quality that is specifically associated with or typical of winter.
-
B.
winterStatus
Indicates the condition, phase, or circumstances associated with the winter season for a given entity or context.
-
C.
winterFrequency
Indicates how often the related event, condition, or phenomenon occurs during the winter season.
-
D.
winterForageDependsOn
Indicates that the availability or quality of winter forage is contingent upon, or influenced by, another factor or resource.
-
E.
wintersIn
Indicates that an entity spends the winter season in a particular place or region.
- 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_69ca82e50ebc81909aa7b260c76bd757 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7df887148190bddc2609bc885cb4 |
completed | March 31, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69cb70b5b5348190b296e0ecec95de60 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:53 p.m.