Triple
T17555805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prepositioning Program |
E427586
|
entity |
| Predicate | supplyTypes |
P49241
|
FINISHED |
| Object | ammunition |
—
|
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: ammunition | Statement: [Prepositioning Program, supplyTypes, ammunition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supplyTypes Context triple: [Prepositioning Program, supplyTypes, ammunition]
-
A.
supplyType
chosen
Indicates the kind or category of supply associated with or provided in a given relationship or context.
-
B.
supplyRole
Indicates that an entity provides or fulfills a specific role within a supply or provisioning relationship to another entity.
-
C.
suppliesTo
Indicates that one entity provides or delivers goods, services, or resources to another entity.
-
D.
supplySituation
Indicates a relationship where one entity provides or makes available needed resources, goods, or services to another under specific conditions or circumstances.
-
E.
suppliesCity
Indicates that one entity provides goods, resources, or services to a city.
- 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_69d889df6dc081908f67dbadc03c07ee |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4562205c08190a7580a762d61b1e3 |
completed | April 19, 2026, 4:12 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fb39948190a82a597c5bac5c57 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:50 a.m.