Triple
T29651510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kennedy tax cut |
E750144
|
entity |
| Predicate | longTermEffectOn |
P40373
|
FINISHED |
| Object | expansion of federal tax base through higher incomes |
—
|
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: expansion of federal tax base through higher incomes | Statement: [Kennedy tax cut, longTermEffectOn, expansion of federal tax base through higher incomes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: longTermEffectOn Context triple: [Kennedy tax cut, longTermEffectOn, expansion of federal tax base through higher incomes]
-
A.
predictedEffect
Indicates that one entity is expected to cause, influence, or result in a particular outcome or consequence for another entity.
-
B.
effectOnUser
Indicates how an action, event, or condition influences or impacts a user.
-
C.
limitedEffectOn
Indicates that one entity’s influence, impact, or consequence on another is small in magnitude, scope, or significance.
-
D.
effectOnSystem
chosen
Indicates the influence, change, or impact that one entity, action, or condition has on the state or behavior of a system.
-
E.
consequenceOfInfluence
Indicates that one event, state, or condition occurs as a result of the influence or impact exerted by another.
- 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_69f0d6226fe881908819197c9ef9ee04 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f66f2505c08190bf02667815ebf89a |
completed | May 2, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69f66abfdaf08190a55f14c70be6fd4d |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 28, 2026, 6:52 p.m.