Triple
T11302073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hurricane Gilbert 1988 flood |
E267618
|
entity |
| Predicate | climateEventType |
P98399
|
FINISHED |
| Object | tropical cyclone–induced flood |
—
|
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: tropical cyclone–induced flood | Statement: [Hurricane Gilbert 1988 flood, climateEventType, tropical cyclone–induced flood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: climateEventType Context triple: [Hurricane Gilbert 1988 flood, climateEventType, tropical cyclone–induced flood]
-
A.
climateChangeEffect
Indicates how climate change influences or alters a particular entity, condition, or process.
-
B.
notableDisasterType
Indicates the specific kind or category of disaster for which something (such as a place, event, or entity) is notable or best known.
-
C.
containsMajorClimatePhenomenon
Indicates that the subject region or area includes or experiences a significant, large-scale climate-related event or pattern.
-
D.
climateDriver
Indicates a factor or process that significantly influences or drives changes in climate conditions.
-
E.
hasExtremeWeatherCharacteristic
Indicates that something possesses a notable or defining feature related to extreme weather conditions.
- 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e9a4aad4819097384e1b591be2e3 |
completed | April 9, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69d787a6ca2c8190afdc24b61ccd3f8a |
completed | April 9, 2026, 11:04 a.m. |
| PDg | Predicate description generation | batch_69d796d049e88190a9fd7508f477f541 |
completed | April 9, 2026, 12:08 p.m. |
Created at: April 8, 2026, 9:32 p.m.