Triple
T10964561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of the United States |
E259061
|
entity |
| Predicate | cannotDirectlyControl |
P47949
|
FINISHED |
| Object | unemployment rate |
—
|
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: unemployment rate | Statement: [President of the United States, cannotDirectlyControl, unemployment rate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cannotDirectlyControl Context triple: [President of the United States, cannotDirectlyControl, unemployment rate]
-
A.
canControl
Indicates that one entity has the ability or authority to direct, manage, or influence the behavior or state of another entity.
-
B.
doesNotControl
chosen
Indicates that one entity lacks authority, influence, or power to direct, manage, or determine the actions or state of another entity.
-
C.
cannotTarget
Indicates that one entity is unable or not permitted to select or act upon another entity as a target.
-
D.
cannot
Indicates that one entity lacks the ability, permission, or possibility to perform an action or participate in a specified relationship with another entity.
-
E.
cannotBeEasilyDisabled
Indicates that the relationship or mechanism cannot be turned off, bypassed, or neutralized without significant effort, expertise, or resources.
- 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_69d6aa88500c819097d7032ca578e74f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d77148c4588190ad0f2b54ee4bab98 |
completed | April 9, 2026, 9:28 a.m. |
| PD | Predicate disambiguation | batch_69d72e8c27cc81908050590b7a04cafd |
completed | April 9, 2026, 4:43 a.m. |
Created at: April 8, 2026, 9:24 p.m.