Triple
T3822147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tax Cuts and Jobs Act of 2017 |
E88596
|
entity |
| Predicate | limitsStateAndLocalTaxDeduction |
P39307
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Tax Cuts and Jobs Act of 2017, limitsStateAndLocalTaxDeduction, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: limitsStateAndLocalTaxDeduction Context triple: [Tax Cuts and Jobs Act of 2017, limitsStateAndLocalTaxDeduction, yes]
-
A.
taxType
Indicates the specific category or classification of tax that applies to an entity, transaction, or amount.
-
B.
jurisdictionLimit
Indicates the maximum scope or boundary within which an authority, organization, or rule is legally empowered to operate or exercise control.
-
C.
taxOn
Indicates that one entity imposes or applies a tax on another entity or item.
-
D.
effectOnTaxes
chosen
Indicates how one entity or action changes, influences, or determines the amount, structure, or treatment of taxes for another entity or situation.
-
E.
hasLocalOrdinances
Indicates that a governing body or jurisdiction has established and enacted specific local ordinances or regulations.
- 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_69aed9538cf881909d9ce8ca4ac7c18c |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef188b474819087680db42b04ecdd |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee74a2bc081909b237df8b1e27653 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:17 p.m.