Triple
T1678345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Boat That Rocked |
E36282
|
entity |
| Predicate | hasSettingAspect |
P3538
|
FINISHED |
| Object | ship-based radio station |
—
|
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: ship-based radio station | Statement: [The Boat That Rocked, hasSettingAspect, ship-based radio station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSettingAspect Context triple: [The Boat That Rocked, hasSettingAspect, ship-based radio station]
-
A.
hasSetting
chosen
Indicates that an entity takes place, occurs, or exists within a particular environment, context, or location.
-
B.
hasAspectSystem
Indicates that an entity possesses or is associated with a particular aspect system, such as a structured set of characteristics, dimensions, or perspectives.
-
C.
hasKeyAspect
Indicates that something possesses a central, defining, or particularly important feature or characteristic.
-
D.
hasNotableSettingBy
Indicates that the subject has a notable or significant setting that was created, designed, or established by the specified entity.
-
E.
hasConfiguration
Indicates that an entity is associated with or defined by a particular configuration or setup.
- 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_69a886139ed081909af0940aa9313512 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aba644070c81908745b56d981fe273 |
completed | March 7, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69aa61b57a6881909373af287ef24799 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:29 p.m.