Triple
T63069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Special Forces Branch |
E1251
|
entity |
| Predicate | training |
P3665
|
FINISHED |
| Object | advanced small-unit tactics |
—
|
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: advanced small-unit tactics | Statement: [Special Forces Branch, training, advanced small-unit tactics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: training Context triple: [Special Forces Branch, training, advanced small-unit tactics]
-
A.
trainingGround
Indicates a location or context where entities engage in practice, drills, or preparation activities to develop or improve skills.
-
B.
trainingInstitution
Indicates that one entity serves as the institution or organization where another entity receives training or education.
-
C.
operation
Indicates that one entity performs, carries out, or controls the functioning of another entity or system.
-
D.
target
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
E.
tracks
Indicates that one entity monitors, follows, or keeps a record of another entity’s state, behavior, or progress over time.
- 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a24fd16c248190a6ee4cd96c388772 |
completed | Feb. 28, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69a24ea3c44081908fa3856969881d1f |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a24fcf5a88819088c5fa4c08476358 |
completed | Feb. 28, 2026, 2:15 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.