Triple
T9914376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hurricane Dorian |
E185829
|
entity |
| Predicate | eyewallReplacementCycles |
P91131
|
FINISHED |
| Object | multiple |
—
|
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: multiple | Statement: [Hurricane Dorian, eyewallReplacementCycles, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eyewallReplacementCycles Context triple: [Hurricane Dorian, eyewallReplacementCycles, multiple]
-
A.
hasTropicalCyclones
Indicates that the specified region or area experiences tropical cyclones as part of its typical weather or climate conditions.
-
B.
strongestStorm
Indicates that one storm is the most intense or powerful compared to a set of other storms.
-
C.
numberOfTropicalDepressions
Indicates the count of tropical depressions associated with or occurring in relation to a given entity or context.
-
D.
numberOfHurricanes
Indicates the total count of hurricanes associated with a specified context, such as a region, time period, or event.
-
E.
numberOfNamedStorms
Indicates the total count of distinct storms that have been formally assigned names within a specified context or period.
- 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_69ca829b45f481909040f7b99a1976ed |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb53ba1ac8190ba655133b81596d7 |
completed | April 2, 2026, 12:15 a.m. |
| PD | Predicate disambiguation | batch_69cd1d8c584081908b73de75eb18e438 |
completed | April 1, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69cd3581a9688190a00cef4c3eebb0ae |
completed | April 1, 2026, 3:10 p.m. |
Created at: March 30, 2026, 8:41 p.m.