Triple
T1885536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sevagram |
E39954
|
entity |
| Predicate | winterTemperatureCharacteristic |
P10789
|
FINISHED |
| Object | mild 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 winters | Statement: [Sevagram, winterTemperatureCharacteristic, mild winters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winterTemperatureCharacteristic Context triple: [Sevagram, winterTemperatureCharacteristic, mild winters]
-
A.
winterCharacteristic
chosen
Indicates a characteristic, feature, or quality that is specifically associated with or typical of winter.
-
B.
wintersIn
Indicates that an entity spends the winter season in a particular place or region.
-
C.
coldestSeason
Indicates the season during which a place or region experiences its lowest typical temperatures compared to other seasons.
-
D.
averageWinterLowTemperature
Indicates the typical minimum temperature experienced during the winter season for a given location or period.
-
E.
averageWinterHighF
Indicates the typical or mean high temperature, measured in degrees Fahrenheit, during the winter season for the referenced entity.
- 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_69a88633e4fc8190b7eb40463e048ec5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb4f53f408190ae30e1a12721e7d7 |
completed | March 7, 2026, 5:17 a.m. |
| PD | Predicate disambiguation | batch_69abafe497a88190a1da6af2888b71b4 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:34 p.m.