Triple
T2633884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brazilian Grand Prix |
E59697
|
entity |
| Predicate | notableWeather |
P42381
|
FINISHED |
| Object | sudden rain 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: sudden rain showers | Statement: [Brazilian Grand Prix, notableWeather, sudden rain showers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableWeather Context triple: [Brazilian Grand Prix, notableWeather, sudden rain showers]
-
A.
snowfallRecord
Indicates that a specific amount of snow has been measured or documented for a particular place and time.
-
B.
maximumRecordedTemperature
Indicates the highest temperature value that has been observed and recorded for a given entity or context.
-
C.
recordHighTemperatureLocation
Indicates the location where the highest recorded temperature occurred.
-
D.
hasExtremeWeatherCharacteristic
Indicates that something possesses a notable or defining feature related to extreme weather conditions.
-
E.
historicalPeak
Indicates that the related value or state represents the highest level ever reached by something within a historical or recorded time frame.
- F. None of above. chosen
Provenance (4 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_69ab4ac8596c8190b34997e73d9e991c |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abdb0e7b888190bfa5d2e33f00ec0f |
completed | March 7, 2026, 8 a.m. |
| PD | Predicate disambiguation | batch_69abd810d7f481908e81c305772c4c14 |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abdb0bf9b881908b239c1310c7bbf3 |
completed | March 7, 2026, 8 a.m. |
Created at: March 6, 2026, 9:50 p.m.