Triple
T22845555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Townsville Airport |
E566205
|
entity |
| Predicate | roleDuringSecondWorldWar |
P16542
|
FINISHED |
| Object | military air base |
—
|
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: military air base | Statement: [Townsville Airport, roleDuringSecondWorldWar, military air base]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleDuringSecondWorldWar Context triple: [Townsville Airport, roleDuringSecondWorldWar, military air base]
-
A.
sideInWorldWarII
Indicates that an entity was aligned with or participated on a particular side during World War II.
-
B.
operatorDuringWorldWarII
Indicates that an entity operated or was active in its role during the period of World War II.
-
C.
statusDuringWorldWarII
Indicates the role, condition, or classification an entity had specifically during the period of World War II.
-
D.
enemyDuringWWII
Indicates that one entity was an enemy of the other during World War II.
-
E.
worldWarIIRole
chosen
Indicates the specific role, position, or function an entity had in relation to World War II.
- 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_69e245869e188190a196584f36e682da |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e882b148190985c085bb1a92aae |
completed | April 29, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69eed2d117088190acbfe130d84f8627 |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:36 p.m.