Triple
T1745131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rudolph |
E38319
|
entity |
| Predicate | associatedWithWeather |
P32056
|
FINISHED |
| Object | fog |
—
|
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: fog | Statement: [Rudolph, associatedWithWeather, fog]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithWeather Context triple: [Rudolph, associatedWithWeather, fog]
-
A.
hasWeather
Indicates that a location or environment is experiencing or characterized by a particular type of weather condition.
-
B.
weatherCondition
Indicates the type of atmospheric state or weather pattern (e.g., sunny, rainy, snowy) affecting a location or time period.
-
C.
hasExtremeWeatherCharacteristic
Indicates that something possesses a notable or defining feature related to extreme weather conditions.
-
D.
hasSevereWeatherRisk
Indicates that an entity is exposed to or associated with a high likelihood of severe or hazardous weather conditions.
-
E.
weatherRole
Indicates a role or function that an entity has in relation to weather conditions or weather-related phenomena.
- 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_69a8862b01a48190ab47209063af82d9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab630e7d008190a8c673665d9672bb |
completed | March 6, 2026, 11:28 p.m. |
| PD | Predicate disambiguation | batch_69aa61c5a18481909bc49e0c54d64314 |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab630cb34881908c9fb7ed5dedcd77 |
completed | March 6, 2026, 11:28 p.m. |
Created at: March 4, 2026, 7:31 p.m.