Triple
T5959970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlotte Hall Military Academy |
E132609
|
entity |
| Predicate | hasMilitaryTraining |
P38925
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Charlotte Hall Military Academy, hasMilitaryTraining, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMilitaryTraining Context triple: [Charlotte Hall Military Academy, hasMilitaryTraining, true]
-
A.
militaryBackground
chosen
Indicates that an entity has prior or current experience, service, or training in a military organization.
-
B.
hasMilitaryStatus
Indicates that an entity possesses a specific military affiliation, role, or status (such as active duty, reserve, or veteran).
-
C.
hasNearbyMilitaryTrainingArea
Indicates that an entity is located close to a designated area used for military training activities.
-
D.
hasMilitaryAuthority
Indicates that one entity possesses formal power or command to direct, control, or make decisions over the military activities or forces of another entity.
-
E.
hasMilitaryAssociation
Indicates a relationship in which an entity is connected or affiliated with a military organization, activity, or function.
- 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_69c0086c2364819091e9fe2f58fa2517 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03fb7f8a88190a8bd45208bda4a03 |
completed | March 22, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69c0335a635881909c58c1ef0f97f1e8 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4:02 p.m.