Triple
T37010168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 131st Training Flight |
E915919
|
entity |
| Predicate | personnelTypeTrained |
P40765
|
FINISHED |
| Object | Air National Guard personnel |
—
|
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: Air National Guard personnel | Statement: [131st Training Flight, personnelTypeTrained, Air National Guard personnel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: personnelTypeTrained Context triple: [131st Training Flight, personnelTypeTrained, Air National Guard personnel]
-
A.
personnelType
Indicates the classification or role category assigned to a person within an organization or system.
-
B.
providesTrainingFor
chosen
Indicates that one entity delivers or conducts training activities intended to develop the skills or knowledge of another entity.
-
C.
hasTrainingType
Indicates that an entity is associated with or characterized by a specific type or category of training.
-
D.
militaryTrainingType
Indicates the specific kind or category of military training associated with an entity or event.
-
E.
hasTrainingRole
Indicates that an entity holds or is assigned a specific role within a training or instructional context.
- 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_69f76e90ed548190b187d2475f5c807d |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb55de3b9c8190a7656aeab3c3ffbc |
completed | May 6, 2026, 2:53 p.m. |
| PD | Predicate disambiguation | batch_69fb35bc92e08190bff447624e2df791 |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:14 p.m.