Triple
T8911451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RAF Biggin Hill |
E212190
|
entity |
| Predicate | hasRadarControlRole |
P86330
|
FINISHED |
| Object | sector 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: sector station | Statement: [RAF Biggin Hill, hasRadarControlRole, sector station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRadarControlRole Context triple: [RAF Biggin Hill, hasRadarControlRole, sector station]
-
A.
hasRadarServices
Indicates that one entity provides or is equipped with radar-based services or capabilities for another entity or context.
-
B.
radarType
Indicates the specific category or classification of radar associated with an entity.
-
C.
radarEquipment
Indicates that one entity is radar equipment used for detecting, tracking, or measuring objects relative to another entity.
-
D.
radarConfiguration
Indicates a relationship where a radar system is associated with or defined by a specific configuration or setup of its operational parameters.
-
E.
radarModel
Indicates that one entity is a radar system and the other is the specific model or type designation of that radar.
- 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_69ca8393b1808190bd4336787ffa2c40 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6523b9348190a7cefac9e73e2004 |
completed | April 1, 2026, 12:21 a.m. |
| PD | Predicate disambiguation | batch_69cc5ecf55248190a29f00fbf99f13c4 |
completed | March 31, 2026, 11:54 p.m. |
| PDg | Predicate description generation | batch_69cc604965c48190bbb6db0ae8108e67 |
completed | April 1, 2026, 12:01 a.m. |
Created at: March 30, 2026, 6:55 p.m.