Triple
T19798964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 111th MI Brigade |
E475618
|
entity |
| Predicate | trainsInDiscipline |
P137368
|
FINISHED |
| Object | all-source intelligence |
—
|
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: all-source intelligence | Statement: [111th MI Brigade, trainsInDiscipline, all-source intelligence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainsInDiscipline Context triple: [111th MI Brigade, trainsInDiscipline, all-source intelligence]
-
A.
alsoTrains
Indicates that an entity, in addition to its primary role or activity, is involved in training another entity.
-
B.
maintainsTrainsFor
Indicates that one entity is responsible for servicing, repairing, or otherwise keeping trains operational for another entity.
-
C.
trainsForOccupation
Indicates that an entity undergoes training or preparation aimed at qualifying for or performing a specific occupation.
-
D.
trainsCategory
Indicates that one entity is a category or type under which the other entity is trained or classified.
-
E.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
- 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_69d8e51b014081908b263e167370529a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e653c930a08190a2263db7170edd71 |
completed | April 20, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69e5305858108190bbbfdb9ba3ab9f80 |
completed | April 19, 2026, 7:43 p.m. |
| PDg | Predicate description generation | batch_69e532bcf41c8190b685b5adf46a60fc |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:49 p.m.