Triple
T7461396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Public Law 110-343 |
E176256
|
entity |
| Predicate | authorizesSpendingLimit |
P7930
|
FINISHED |
| Object | 700 billion U.S. dollars |
—
|
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: 700 billion U.S. dollars | Statement: [Public Law 110-343, authorizesSpendingLimit, 700 billion U.S. dollars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: authorizesSpendingLimit Context triple: [Public Law 110-343, authorizesSpendingLimit, 700 billion U.S. dollars]
-
A.
authorizedSpending
chosen
Indicates that an entity has been granted permission to spend or allocate a specified amount of resources, typically funds, under defined conditions.
-
B.
deficitLimit
Indicates a constraint or maximum allowable amount on how large a deficit (shortfall or negative balance) may be.
-
C.
moneyBillsRestriction
Indicates a limitation or control placed on the use, amount, or handling of money bills in a given context.
-
D.
isLimitOf
Indicates that one quantity, function, or sequence approaches a particular value as its input or index approaches some specified point or condition.
-
E.
supportsSpendingCategory
Indicates that one entity allows, enables, or is compatible with making expenditures in a specified spending category.
- 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_69c69f21632481908bf83f6c6da897e3 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f3d6cf8c8190a31cac121d151d78 |
completed | March 27, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69c6f03bad9c8190bdd5abb86d37df47 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:38 p.m.