Triple
T2209021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Furious Fifties |
E50869
|
entity |
| Predicate | hasPrevailingWindType |
P2125
|
FINISHED |
| Object | strong westerly gales |
—
|
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: strong westerly gales | Statement: [Furious Fifties, hasPrevailingWindType, strong westerly gales]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrevailingWindType Context triple: [Furious Fifties, hasPrevailingWindType, strong westerly gales]
-
A.
prevailingSurfaceWinds
chosen
Indicates the typical or most frequently occurring wind direction and speed that dominate at a given location over a specified period.
-
B.
hasWindFarm
Indicates that one entity possesses, hosts, or contains a wind farm as part of its assets, infrastructure, or territory.
-
C.
hasWindmill
Indicates that one entity possesses, contains, or features a windmill as part of it or on its premises.
-
D.
windmillType
Indicates that one entity is classified as a specific type or category of windmill in relation to another entity.
-
E.
hasExtremeWeatherCharacteristic
Indicates that something possesses a notable or defining feature related to extreme weather conditions.
- 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_69a88b06709c8190978fb2418470d1b6 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc1baa0948190b07ffc347a4f714e |
completed | March 7, 2026, 6:12 a.m. |
| PD | Predicate disambiguation | batch_69abbda8a6dc8190aa855ce2d17194b1 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.