Triple
T7252815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mosquito NF Mk II |
E157644
|
entity |
| Predicate | radarAntennaType |
P13776
|
FINISHED |
| Object | external aerial arrays on the nose |
—
|
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: external aerial arrays on the nose | Statement: [Mosquito NF Mk II, radarAntennaType, external aerial arrays on the nose]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: radarAntennaType Context triple: [Mosquito NF Mk II, radarAntennaType, external aerial arrays on the nose]
-
A.
antennaType
chosen
Indicates the specific kind or category of antenna associated with an entity or connection.
-
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.
radarModel
Indicates that one entity is a radar system and the other is the specific model or type designation of that radar.
-
E.
radarConfiguration
Indicates a relationship where a radar system is associated with or defined by a specific configuration or setup of its operational parameters.
- 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_69c6882d81d4819085f7ff862951ee4f |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea9d41908190bb76c6a5b9d5b1a2 |
completed | March 27, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69c6e7666ffc81908bf643d8257e6337 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:56 p.m.