Triple
T17196910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Halsey’s Typhoon |
E417374
|
entity |
| Predicate | weatherType |
P1702
|
FINISHED |
| Object | intense tropical storm |
—
|
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: intense tropical storm | Statement: [Halsey’s Typhoon, weatherType, intense tropical storm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: weatherType Context triple: [Halsey’s Typhoon, weatherType, intense tropical storm]
-
A.
weatherCondition
chosen
Indicates the type of atmospheric state or weather pattern (e.g., sunny, rainy, snowy) affecting a location or time period.
-
B.
weatherRole
Indicates a role or function that an entity has in relation to weather conditions or weather-related phenomena.
-
C.
weatherCapability
Indicates that an entity has the ability or functionality to provide, process, or otherwise handle weather-related information or services.
-
D.
hasWeather
Indicates that a location or environment is experiencing or characterized by a particular type of weather condition.
-
E.
weatherConsideration
Indicates that certain conditions, decisions, or actions take into account or are influenced by the current or expected weather.
- 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_69d886d6ba8c819093215917b3d01689 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42dab718c8190b6f5b08189cf2eb2 |
completed | April 19, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69e383141ae0819096acd71683637cbc |
completed | April 18, 2026, 1:11 p.m. |
Created at: April 10, 2026, 5:38 a.m.