Triple
T263673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Insurance Contributions Act taxes |
E5806
|
entity |
| Predicate | revenueUse |
P9389
|
FINISHED |
| Object | trust funds for Social Security |
—
|
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: trust funds for Social Security | Statement: [Federal Insurance Contributions Act taxes, revenueUse, trust funds for Social Security]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: revenueUse Context triple: [Federal Insurance Contributions Act taxes, revenueUse, trust funds for Social Security]
-
A.
revenue
Indicates the amount of income generated by an entity from its business activities or operations over a specified period.
-
B.
revenueLevel
Indicates the relative amount or tier of revenue associated with an entity or activity.
-
C.
actualUse
Indicates that an entity is currently being used or utilized in practice, as opposed to being merely available, planned, or potential.
-
D.
majorRevenueSource
Indicates that one entity serves as the primary or dominant source of revenue for another entity.
-
E.
economicUse
Indicates that one entity utilizes another for economic purposes, such as production, trade, revenue generation, or cost-saving activities.
- F. None of above. chosen
Provenance (4 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_69a258dd8ea08190ac554a1cc8dfd8c3 |
completed | Feb. 28, 2026, 2:54 a.m. |
| NER | Named-entity recognition | batch_69a25d8e809881908a58c9a4e3ba07c3 |
completed | Feb. 28, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69a25b6e07748190834022a65ba6d803 |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25d0ec71081908478c800be4f7bb0 |
completed | Feb. 28, 2026, 3:12 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.