Triple
T2709794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | eastern North Pacific Ocean |
E59830
|
entity |
| Predicate | hasPrevailingWinds |
P2125
|
FINISHED |
| Object | trade winds |
—
|
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: trade winds | Statement: [eastern North Pacific Ocean, hasPrevailingWinds, trade winds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrevailingWinds Context triple: [eastern North Pacific Ocean, hasPrevailingWinds, trade winds]
-
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.
hasWindPattern
Indicates that one entity exhibits, is characterized by, or is associated with a particular pattern of wind behavior.
-
C.
hasMinimumWeatherRequirements
Indicates that a subject is associated with the lowest acceptable set of weather conditions required for a particular activity, operation, or state to occur.
-
D.
hasWindFarm
Indicates that one entity possesses, hosts, or contains a wind farm as part of its assets, infrastructure, or territory.
-
E.
hasSevereWeatherRisk
Indicates that an entity is exposed to or associated with a high likelihood of severe or hazardous 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_69ab4ac92a088190bc74bca14038e3de |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda7771a4819081904bd6b818b81b |
completed | March 7, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69abd8224c688190bb4a362360b03007 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:55 p.m.