Triple
T226530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montpelier, Vermont |
E4325
|
entity |
| Predicate | averageWinterConditions |
P2900
|
FINISHED |
| Object | cold and snowy |
—
|
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: cold and snowy | Statement: [Montpelier, Vermont, averageWinterConditions, cold and snowy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageWinterConditions Context triple: [Montpelier, Vermont, averageWinterConditions, cold and snowy]
-
A.
snowCover
Indicates that one entity is covered by or blanketed with snow.
-
B.
averageTemperature
Indicates the typical or mean temperature value associated with an entity over a specified period or context.
-
C.
hasAverageSpringTemperature
Indicates that an entity is associated with a specific average temperature value measured over the spring season.
-
D.
requiresFrostFreeSeason
Indicates that the subject depends on a period without frost to grow, develop, or function properly.
-
E.
environmentalCondition
chosen
Indicates the state or characteristics of the surrounding physical environment that affect or describe a situation, process, or 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_69a257363ffc81909757bde7ab3404da |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25d10ac248190a98dedabf5358668 |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b5877588190af694d060377f027 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.