Triple
T26894278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacobabad |
E677858
|
entity |
| Predicate | hasExtremeWeatherType |
P17982
|
FINISHED |
| Object | heatwaves |
—
|
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: heatwaves | Statement: [Jacobabad, hasExtremeWeatherType, heatwaves]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExtremeWeatherType Context triple: [Jacobabad, hasExtremeWeatherType, heatwaves]
-
A.
hasExtremeWeatherCharacteristic
chosen
Indicates that something possesses a notable or defining feature related to extreme weather conditions.
-
B.
hasSevereWeatherRisk
Indicates that an entity is exposed to or associated with a high likelihood of severe or hazardous weather conditions.
-
C.
hasHighPrecipitation
Indicates that a location or time period experiences a large amount of precipitation, such as rain or snow, relative to a defined standard or average.
-
D.
hasWinterPhenomenon
Indicates that an entity experiences or is characterized by a particular phenomenon occurring during the winter season.
-
E.
hasSignificantWeatherInfluence
Indicates that one entity exerts a substantial impact on the weather conditions or patterns experienced by another entity or region.
- 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_69eee9befee48190a26f214faa867be7 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f68f670b608190a0b6ab60d722b4e0 |
completed | May 2, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69f68b78f29481908cc8f390496dee97 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 27, 2026, 5:47 a.m.