Triple
T6083876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katia |
E135587
|
entity |
| Predicate | stormNameList |
P68552
|
FINISHED |
| Object | Atlantic tropical cyclone naming lists |
—
|
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: Atlantic tropical cyclone naming lists | Statement: [Katia, stormNameList, Atlantic tropical cyclone naming lists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stormNameList Context triple: [Katia, stormNameList, Atlantic tropical cyclone naming lists]
-
A.
numberOfNamedStorms
Indicates the total count of distinct storms that have been formally assigned names within a specified context or period.
-
B.
strongestStorm
Indicates that one storm is the most intense or powerful compared to a set of other storms.
-
C.
typicalStormType
Indicates the kind of storm that is most commonly or characteristically associated with a given context or location.
-
D.
stormedOn
Indicates that a storm or severe weather event occurred affecting or impacting a particular entity or location.
-
E.
numberOfHurricanes
Indicates the total count of hurricanes associated with a specified context, such as a region, time period, or event.
- 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_69c0087bcc788190b20f093d3a6c60ec |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c057877b448190aa12d2484102eeaa |
completed | March 22, 2026, 8:56 p.m. |
| PD | Predicate disambiguation | batch_69c049f3b1ec8190bea67a7bec6442a5 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8d4a148190bd8f95caae978e1b |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:11 p.m.