Triple
T36523650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Army Tactical Training Center |
E900241
|
entity |
| Predicate | includesTrainingAreaType |
—
|
GENERATED |
| Object | field training areas |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesTrainingAreaType Context triple: [Army Tactical Training Center, includesTrainingAreaType, field training areas]
-
A.
includesAreaType
chosen
Indicates that one entity encompasses or contains another entity of a specified area type within its scope or boundaries.
-
B.
hasTrainingType
Indicates that an entity is associated with or characterized by a specific type or category of training.
-
C.
trainingLocationType
Indicates the type or category of place where a training activity occurs.
-
D.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
E.
hasStudyAreaType
Indicates that an entity’s study area is classified as a specific type or category (e.g., lab, field site, classroom).
- F. None of above.
Provenance (1 batch)
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_69f76e5eedb88190a393b8c623f71dd7 |
completed | May 3, 2026, 3:48 p.m. |
Created at: May 3, 2026, 4:11 p.m.