Triple
T11528776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Aral Sea |
E273363
|
entity |
| Predicate | hasClimateEffect |
P3009
|
FINISHED |
| Object | more extreme local temperatures |
—
|
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: more extreme local temperatures | Statement: [South Aral Sea, hasClimateEffect, more extreme local temperatures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClimateEffect Context triple: [South Aral Sea, hasClimateEffect, more extreme local temperatures]
-
A.
hasClimateInfluence
chosen
Indicates that one entity affects or contributes to the climate characteristics or climate-related conditions of another entity.
-
B.
hasClimate
Indicates that an entity possesses or is characterized by a particular type of climate or climatic conditions.
-
C.
hasClimateContext
Indicates that something is associated with, influenced by, or relevant to climate-related conditions, factors, or considerations.
-
D.
climateChangeEffect
Indicates how climate change influences or alters a particular entity, condition, or process.
-
E.
hasClimateSystem
Indicates that one entity possesses or is characterized by a particular climate system.
- 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_69d6aae3fbec8190a14632a5df2538b6 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d883972b10819093bd09cf8406671c |
completed | April 10, 2026, 4:59 a.m. |
| PD | Predicate disambiguation | batch_69d80879fdb48190be6dacc8aa63c809 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:37 p.m.