Triple
T30883833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RAF Exeter |
E786698
|
entity |
| Predicate | airDefenceSector |
P170269
|
FINISHED |
| Object | South West England |
—
|
NE NERFINISHED |
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: South West England | Statement: [RAF Exeter, airDefenceSector, South West England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airDefenceSector Context triple: [RAF Exeter, airDefenceSector, South West England]
-
A.
airDefenseSystem
Indicates a defensive military system designed to detect, track, and engage airborne threats such as aircraft or missiles.
-
B.
airDefenseSystemComponent
Indicates that one entity is a component or subsystem of an air defense system associated with another entity.
-
C.
airfieldDefended
Indicates that defensive measures or forces are in place to protect an airfield from attack or unauthorized intrusion.
-
D.
airDefenseArmament
Indicates the weapons or systems specifically equipped on an entity for defending against aerial threats such as aircraft or missiles.
-
E.
airDefenseRangeClass
Indicates the classification category of the effective range within which an air defense system can engage aerial targets.
- 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_69f224bae17c8190bb3a6a28e3d019df |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69204be748190a6a2a401d81c1218 |
completed | May 3, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69f68b7ec098819080480998038de940 |
completed | May 2, 2026, 11:40 p.m. |
| PDg | Predicate description generation | batch_69f68c517f308190873c1c7e05a0c6d0 |
completed | May 2, 2026, 11:44 p.m. |
Created at: April 29, 2026, 8:48 p.m.