Triple
T21512242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BWh |
E530754
|
entity |
| Predicate | hasTypicalWeatherHazard |
P132755
|
FINISHED |
| Object | heat waves |
—
|
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: heat waves | Statement: [BWh, hasTypicalWeatherHazard, heat waves]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalWeatherHazard Context triple: [BWh, hasTypicalWeatherHazard, heat waves]
-
A.
hasSevereWeatherRisk
Indicates that an entity is exposed to or associated with a high likelihood of severe or hazardous weather conditions.
-
B.
hasExtremeWeatherCharacteristic
Indicates that something possesses a notable or defining feature related to extreme weather conditions.
-
C.
hasSnowRisk
Indicates that there is a potential or likelihood of snow affecting the related entity or situation.
-
D.
typicalWeatherFeature
chosen
Indicates a weather condition or pattern that commonly characterizes a place or time period.
-
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_69e0c45c81f08190a6b8bbb70a45aae7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea8779c081908171c58d345d54ae |
completed | April 23, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69e6320043bc81909417c41a718652ba |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:25 p.m.