Triple
T31248366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nile inundation system |
E796748
|
entity |
| Predicate | riskIfTooHigh |
P171632
|
FINISHED |
| Object | destructive flooding |
—
|
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: destructive flooding | Statement: [Nile inundation system, riskIfTooHigh, destructive flooding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riskIfTooHigh Context triple: [Nile inundation system, riskIfTooHigh, destructive flooding]
-
A.
riskIfTooLow
Indicates that a risk or adverse consequence arises when the associated quantity, level, or condition falls below a specified threshold.
-
B.
riskHighlighted
Indicates that a particular risk has been identified and specially marked for attention or emphasis.
-
C.
riskTaken
Indicates that an entity has undertaken an action or decision involving exposure to potential loss, harm, or uncertainty.
-
D.
riskIfFailure
Indicates that one entity faces potential negative consequences or harm if another entity fails or an attempted action is unsuccessful.
-
E.
riskLevel
Indicates the degree of potential harm, loss, or adverse outcome associated with a particular situation, action, or entity.
- F. None of above. chosen
Provenance (4 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_69f224dc84d0819081f1cb6f9127e6b1 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6a1ac56b88190a820434b65c9fa23 |
completed | May 3, 2026, 1:15 a.m. |
| PD | Predicate disambiguation | batch_69f69fe463248190aa78128abeab1183 |
completed | May 3, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69f6a0e920cc8190a943fdd0594906c5 |
completed | May 3, 2026, 1:12 a.m. |
Created at: April 29, 2026, 9:11 p.m.