Triple
T24899524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buk-M2E |
E623534
|
entity |
| Predicate | systemComposition |
P840
|
FINISHED |
| Object | target acquisition radar |
—
|
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: target acquisition radar | Statement: [Buk-M2E, systemComposition, target acquisition radar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: systemComposition Context triple: [Buk-M2E, systemComposition, target acquisition radar]
-
A.
serviceComposition
Indicates that one service is formed by combining or orchestrating multiple other services to function together as a unified whole.
-
B.
computerSystem
Indicates a relationship where an entity functions as or is classified as a computer system, typically comprising hardware, software, and related components that operate together.
-
C.
designedAsPartOfSystemBy
Indicates that an entity was intentionally created as a component or module within a larger system by a specific designer or designing agent.
-
D.
partOfSystem
chosen
Indicates that one entity functions as a component or subsystem within the structure or organization of another entity.
-
E.
modelsSystemsWith
Indicates that one entity creates or uses a representation or abstraction to describe, analyze, or simulate another system.
- 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_69e2fac797cc8190b30d77f4121099ac |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f47b865df48190bf4b6d3e9f9305e6 |
completed | May 1, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69f4682c8a3c8190adbfaac99474eaaf |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 18, 2026, 5:26 a.m.