Triple
T18650144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AIM-54 Phoenix |
E455909
|
entity |
| Predicate | maxTargetsTrackedPerF14 |
P9099
|
FINISHED |
| Object | up to 24 targets |
—
|
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: up to 24 targets | Statement: [AIM-54 Phoenix, maxTargetsTrackedPerF14, up to 24 targets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maxTargetsTrackedPerF14 Context triple: [AIM-54 Phoenix, maxTargetsTrackedPerF14, up to 24 targets]
-
A.
targetedAircraft
Indicates that one entity has selected or designated an aircraft as the object of an attack, tracking, or other directed action.
-
B.
fighterNumber
Indicates the identifying number assigned to a fighter within a given context or event.
-
C.
numberOfTransponders
Indicates the quantity of transponders associated with or contained by a given entity.
-
D.
numberOfTargets
chosen
Indicates the quantity of target entities associated with or affected by a given subject or event.
-
E.
squadronSize
Indicates the number of units or members that make up a particular squadron.
- 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_69d8d38ea1e88190997e9b231190ba6f |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e55010d27c8190aad8d3c9e8cd31b2 |
completed | April 19, 2026, 9:58 p.m. |
| PD | Predicate disambiguation | batch_69e478d85864819093cbad5ed9b54878 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:47 a.m.