Triple
T2209074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | the Screaming Sixties |
E50870
|
entity |
| Predicate | hasWindPattern |
P37481
|
FINISHED |
| Object | strong circumpolar westerlies |
—
|
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 circumpolar westerlies | Statement: [the Screaming Sixties, hasWindPattern, strong circumpolar westerlies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWindPattern Context triple: [the Screaming Sixties, hasWindPattern, strong circumpolar westerlies]
-
A.
hasWindFarm
Indicates that one entity possesses, hosts, or contains a wind farm as part of its assets, infrastructure, or territory.
-
B.
hasSpiralPattern
Indicates that one entity exhibits or possesses a spiral-shaped pattern or arrangement in relation to another.
-
C.
hasWindmill
Indicates that one entity possesses, contains, or features a windmill as part of it or on its premises.
-
D.
hasBearingPattern
Indicates a relationship where an object or system exhibits or is characterized by a specific bearing arrangement or configuration pattern.
-
E.
hatPattern
Indicates that one entity has a hat characterized by a specific pattern or design.
- 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_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. |
| PDg | Predicate description generation | batch_69abc1b912c08190b9d7bc9230e49d1d |
completed | March 7, 2026, 6:12 a.m. |
Created at: March 4, 2026, 7:46 p.m.