Triple
T32445339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saharan Air Layer |
E829127
|
entity |
| Predicate | affectsAirQuality |
P5628
|
FINISHED |
| Object | degraded visibility |
—
|
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: degraded visibility | Statement: [Saharan Air Layer, affectsAirQuality, degraded visibility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affectsAirQuality Context triple: [Saharan Air Layer, affectsAirQuality, degraded visibility]
-
A.
hasEnvironmentalImpactOn
chosen
Indicates that one entity affects or alters the environmental conditions, quality, or ecological state of another entity.
-
B.
pollutionLevel
Indicates the degree or intensity of environmental contamination present in a given context or location.
-
C.
hasAirQualityMonitoring
Indicates that an entity is equipped with or participates in a system or process for monitoring and measuring air quality.
-
D.
pollutionHealthEffect
Indicates the impact that a given source or level of pollution has on the health or well-being of affected entities.
-
E.
pollutionTolerance
Indicates the degree to which an entity can withstand or remain unaffected by environmental pollution without adverse effects.
- 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_69f3491d2e5c819092b1c9535beff8ec |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f74062b9388190b30546cf700a825c |
completed | May 3, 2026, 12:32 p.m. |
| PD | Predicate disambiguation | batch_69f73c802b848190b61a416b7488bd96 |
completed | May 3, 2026, 12:16 p.m. |
Created at: May 1, 2026, 12:56 a.m.