Triple
T44430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Directorate of Analysis |
E871
|
entity |
| Predicate | hasObjective |
P1415
|
FINISHED |
| Object | provide timely intelligence assessments |
—
|
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: provide timely intelligence assessments | Statement: [Directorate of Analysis, hasObjective, provide timely intelligence assessments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasObjective Context triple: [Directorate of Analysis, hasObjective, provide timely intelligence assessments]
-
A.
hasPrimaryGoal
chosen
Indicates that an entity’s main or most important objective is the specified goal.
-
B.
mission
Indicates that an entity is assigned or engaged in a specific task, operation, or purpose-directed undertaking.
-
C.
target
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
D.
hasNotableSubject
Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
-
E.
hasChallenge
Indicates that an entity faces, experiences, or is confronted with a particular difficulty, obstacle, or problem.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24ba7016481909d595402712db6e2 |
completed | Feb. 28, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69a24abbd32c81908cec461d9097662e |
completed | Feb. 28, 2026, 1:54 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.