Triple
T226531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montpelier, Vermont |
E4325
|
entity |
| Predicate | averageSummerConditions |
P2900
|
FINISHED |
| Object | warm and humid |
—
|
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: warm and humid | Statement: [Montpelier, Vermont, averageSummerConditions, warm and humid]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageSummerConditions Context triple: [Montpelier, Vermont, averageSummerConditions, warm and humid]
-
A.
averageTemperature
Indicates the typical or mean temperature value associated with an entity over a specified period or context.
-
B.
summerHomeOf
Indicates that a location serves as a seasonal or vacation residence for a person or group, specifically used during the summer.
-
C.
hasAverageSpringTemperature
Indicates that an entity is associated with a specific average temperature value measured over the spring season.
-
D.
averageHighTemperatureInJuly
Indicates the typical or mean value of the highest daily temperatures recorded during the month of July for a given location.
-
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.