Triple
T23182783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Square Payroll |
E579504
|
entity |
| Predicate | complianceScope |
P23438
|
FINISHED |
| Object | U.S. payroll tax regulations |
—
|
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: U.S. payroll tax regulations | Statement: [Square Payroll, complianceScope, U.S. payroll tax regulations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: complianceScope Context triple: [Square Payroll, complianceScope, U.S. payroll tax regulations]
-
A.
providesCompliance
Indicates that one entity supplies or ensures adherence to required rules, standards, or regulations for another entity.
-
B.
certificationScope
chosen
Indicates the specific range, domain, or subject matter that a given certification covers or applies to.
-
C.
complianceApproach
Indicates the method or strategy an entity uses to meet, adhere to, or enforce specified rules, standards, or regulatory requirements.
-
D.
indicatesComplianceWith
Indicates that one entity conforms to, satisfies, or adheres to the rules, standards, or requirements specified by another entity or framework.
-
E.
scopeOfUse
Indicates the range, context, or conditions under which something is intended, allowed, or applicable to be used.
- 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_69e245ff8000819090d12008805315b7 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f705c14819082c8580a03ed6286 |
completed | April 29, 2026, 4:56 a.m. |
| PD | Predicate disambiguation | batch_69ef8a041c0081909afb670d17a5aaba |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 4:05 p.m.