Triple
T8011951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bermuda International Airport |
E186513
|
entity |
| Predicate | convertedToCivilUse |
P23908
|
FINISHED |
| Object | post-World War II |
—
|
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: post-World War II | Statement: [Bermuda International Airport, convertedToCivilUse, post-World War II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: convertedToCivilUse Context triple: [Bermuda International Airport, convertedToCivilUse, post-World War II]
-
A.
civilianUse
chosen
Indicates that something is intended for, suitable for, or actually used by civilians rather than military or combat purposes.
-
B.
convertedBy
Indicates that one entity has been transformed or changed in form, state, or representation through the action or process performed by another entity.
-
C.
reconvertedTo
Indicates that something has been changed back or restored to a previous state, form, or condition it once had.
-
D.
hasSecularUse
Indicates that something is used in a non-religious, worldly, or secular context or purpose.
-
E.
civilianVariant
Indicates that one entity is a civilian version or non-military counterpart of another entity.
- 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_69ca82abaffc8190ab8af79cdbc31ab3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3d722fbc8190b22745b581421f16 |
completed | March 31, 2026, 3:20 a.m. |
| PD | Predicate disambiguation | batch_69cb048c9f488190b4fb8917a9c21bc5 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:19 p.m.