Triple
T319847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Shader |
E7788
|
entity |
| Predicate | targetType |
P9903
|
FINISHED |
| Object | ISIS command and control facilities |
—
|
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: ISIS command and control facilities | Statement: [Operation Shader, targetType, ISIS command and control facilities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetType Context triple: [Operation Shader, targetType, ISIS command and control facilities]
-
A.
primaryTargetType
chosen
Indicates the main category or type of entity that is the principal focus or intended recipient of an action, effect, or operation.
-
B.
target
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
C.
componentType
Indicates that one entity specifies or classifies the kind or category of component that another entity represents or uses.
-
D.
termType
Indicates the classification or category of a term within a system, specifying what kind of term it is (e.g., type, role, or function) in relation to others.
-
E.
terminusType
Indicates the specific kind or role of an endpoint or terminal within a route, network, or process.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ea7edbc48190b9031bd1af48f72a |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e946607081909c8b97473aaf8d1b |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.