Triple
T16488021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 40th Paratroop Battalion |
E400496
|
entity |
| Predicate | paratroopTraining |
P123717
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [40th Paratroop Battalion, paratroopTraining, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: paratroopTraining Context triple: [40th Paratroop Battalion, paratroopTraining, yes]
-
A.
paratroopCapacity
Indicates the maximum number of paratroopers or amount of airborne troops that something (typically a vehicle or vessel) is capable of carrying or deploying.
-
B.
parachuteSystem
Indicates that one entity functions as a parachute system used to safely decelerate or recover another entity.
-
C.
trainingGround
Indicates a location or context where entities engage in practice, drills, or preparation activities to develop or improve skills.
-
D.
airborneForces
Indicates that military forces are deployed, transported, or operating via aircraft, typically inserted from the air into an operational area.
-
E.
trainingGroundFor
Indicates that one entity serves as a place or context where another entity is trained, prepared, or developed.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e084f388190887dfb3f6928f506 |
completed | April 18, 2026, 7:08 a.m. |
| PD | Predicate disambiguation | batch_69e296902d6c8190884ddb612b8c5b36 |
completed | April 17, 2026, 8:22 p.m. |
| PDg | Predicate description generation | batch_69e2d7f97e548190a474691a152bd8e8 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:13 a.m.