Triple
T32179100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Employee Retention Credit |
E821933
|
entity |
| Predicate | maximumCredit2021PerQuarterPerEmployee |
P185665
|
FINISHED |
| Object | 7000 USD |
—
|
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: 7000 USD | Statement: [Employee Retention Credit, maximumCredit2021PerQuarterPerEmployee, 7000 USD]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumCredit2021PerQuarterPerEmployee Context triple: [Employee Retention Credit, maximumCredit2021PerQuarterPerEmployee, 7000 USD]
-
A.
maximumCredit2020PerEmployee
Indicates the highest amount of credit that can be claimed for each individual employee for the year 2020.
-
B.
statutoryLimitPerIncidentUSD
Indicates the maximum monetary amount, in U.S. dollars, that is legally allowed to be claimed or paid for a single incident under a specific statute or regulation.
-
C.
annualQuotaNumber
Indicates the specific numeric value assigned as an entity’s quota for a given year.
-
D.
maximumAnnualPurchaseLimitPerSSN
Indicates the highest total amount that may be purchased within a year by any single individual, as identified by their Social Security Number.
-
E.
maximumGrantAmount
Indicates the highest monetary value that can be awarded or granted under a specific grant, program, or agreement.
- 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_69f3490755288190aee11740a34862f9 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f7c33d59808190b647989a093f3488 |
completed | May 3, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b6e7a881908deb96bedb2713f4 |
completed | May 3, 2026, 9:44 p.m. |
| PDg | Predicate description generation | batch_69f7c29cf36481908e472d4dcb5573b9 |
completed | May 3, 2026, 9:48 p.m. |
Created at: May 1, 2026, 12:34 a.m.