Triple
T16295552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RAF Coningsby |
E395636
|
entity |
| Predicate | QuickReactionAlertCoverage |
P122567
|
FINISHED |
| Object | southern United Kingdom |
—
|
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: southern United Kingdom | Statement: [RAF Coningsby, QuickReactionAlertCoverage, southern United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: QuickReactionAlertCoverage Context triple: [RAF Coningsby, QuickReactionAlertCoverage, southern United Kingdom]
-
A.
mediaCoverageControversy
Indicates that media coverage is associated with, contributes to, or centers around a controversy involving the related entities.
-
B.
mediaAttentionLevel
Indicates the degree or intensity of attention or coverage that media outlets give to a particular subject or entity.
-
C.
mediaCoverageAs
Indicates that one entity provides or receives media coverage in the role, capacity, or format specified by another entity.
-
D.
mediaCoverageFocus
Indicates the primary topic, subject, or aspect that media coverage is centered on or emphasizes.
-
E.
mediaCoverage
Indicates that one entity reports on, documents, or broadcasts information about another entity through news or media channels.
- 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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e25e2d08108190bab1b3325923af1d |
completed | April 17, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69e219fa5508819097e9d383348bf174 |
completed | April 17, 2026, 11:31 a.m. |
| PDg | Predicate description generation | batch_69e21e56e0348190a3d9475360231a70 |
completed | April 17, 2026, 11:49 a.m. |
Created at: April 10, 2026, 5:06 a.m.