Triple
T6648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Social Security Act of 1935 |
E132
|
entity |
| Predicate | fundingMechanism |
P59
|
FINISHED |
| Object | payroll tax on employers |
—
|
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: payroll tax on employers | Statement: [Social Security Act of 1935, fundingMechanism, payroll tax on employers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fundingMechanism Context triple: [Social Security Act of 1935, fundingMechanism, payroll tax on employers]
-
A.
fundingModel
chosen
Indicates how an entity is financially supported or sustained, such as through specific revenue sources, payment structures, or funding mechanisms.
-
B.
fundedBy
Indicates that an entity receives financial support or resources from another entity.
-
C.
funds
Indicates that one entity provides financial resources or monetary support to another entity or activity.
-
D.
capital
Indicates that one place serves as the official seat of government or primary administrative center for another political entity.
-
E.
donated
Indicates that one entity voluntarily gave something of value (such as money, goods, or time) to another entity, typically without expecting anything in return.
- 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_69a23bb612708190b09f25385e4b63d1 |
completed | Feb. 28, 2026, 12:49 a.m. |
| NER | Named-entity recognition | batch_69a2421836f08190b54fc40edeb1a96b |
completed | Feb. 28, 2026, 1:17 a.m. |
| PD | Predicate disambiguation | batch_69a23fe064c881909496fd0e6b0e18d7 |
completed | Feb. 28, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 12:54 a.m.