Triple
T13075136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Omnibus Budget Reconciliation Act of 1985 |
E329552
|
entity |
| Predicate | affectedProgramType |
P13559
|
FINISHED |
| Object | mandatory spending programs |
—
|
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: mandatory spending programs | Statement: [Omnibus Budget Reconciliation Act of 1985, affectedProgramType, mandatory spending programs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affectedProgramType Context triple: [Omnibus Budget Reconciliation Act of 1985, affectedProgramType, mandatory spending programs]
-
A.
affectsProgram
chosen
Indicates that one entity produces an influence or change on a program, altering its behavior, state, or outcome.
-
B.
affectedProvision
Indicates that a particular legal provision is impacted, modified, or influenced by another action, decision, or provision.
-
C.
areAffectedBy
Indicates that one entity experiences an effect, influence, or impact as a result of another entity or event.
-
D.
affectedCompany
Indicates that a company is impacted or influenced by a particular event, action, or entity.
-
E.
affectedFunction
Indicates that one entity has an impact on, alters, or impairs the operation or behavior of another entity’s function.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d98117209081908272021013df2222 |
completed | April 10, 2026, 11 p.m. |
| PD | Predicate disambiguation | batch_69d9803d46688190bac6b7d208f08d01 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9 p.m.