Triple
T11993845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qattara Depression Project |
E285477
|
entity |
| Predicate | potentialImpact |
P51728
|
FINISHED |
| Object | regional climate modification |
—
|
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: regional climate modification | Statement: [Qattara Depression Project, potentialImpact, regional climate modification]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: potentialImpact Context triple: [Qattara Depression Project, potentialImpact, regional climate modification]
-
A.
impactOutcome
Indicates that one entity produces an effect or influence that changes the result, consequence, or final state of another entity or situation.
-
B.
impactCategory
chosen
Indicates the type or domain of effect that one entity or action has on another, classifying the nature of its impact.
-
C.
recognizesImpactOn
Indicates that one entity acknowledges or understands the effect or consequences it has on another entity or situation.
-
D.
majorImpact
Indicates that one entity has a significant, highly influential, or transformative effect on another entity or outcome.
-
E.
indirectImpactOn
Indicates that one entity affects another entity’s state, condition, or outcome through one or more intermediate factors rather than through a direct interaction.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903b11ac481909866b611380792e7 |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d902abca70819098291aa51b593708 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:46 p.m.