Triple
T320927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | April |
E6412
|
entity |
| Predicate | hasTypicalWeatherDescription |
P1702
|
FINISHED |
| Object | showers |
—
|
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: showers | Statement: [April, hasTypicalWeatherDescription, showers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalWeatherDescription Context triple: [April, hasTypicalWeatherDescription, showers]
-
A.
hasWeather
Indicates that a location or environment is experiencing or characterized by a particular type of weather condition.
-
B.
weatherCondition
chosen
Indicates the type of atmospheric state or weather pattern (e.g., sunny, rainy, snowy) affecting a location or time period.
-
C.
typicalStormType
Indicates the kind of storm that is most commonly or characteristically associated with a given context or location.
-
D.
hasClimate
Indicates that an entity possesses or is characterized by a particular type of climate or climatic conditions.
-
E.
seasonTypicalStartMonth
Indicates the calendar month in which a particular season usually begins.
- 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea8047c08190872c875e00f6e7dd |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e946607081909c8b97473aaf8d1b |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.