Triple
T13857447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diversity Immigrant Visa |
E333101
|
entity |
| Predicate | annualQuota |
P52204
|
FINISHED |
| Object | up to 55,000 immigrant visas per fiscal year |
—
|
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: up to 55,000 immigrant visas per fiscal year | Statement: [Diversity Immigrant Visa, annualQuota, up to 55,000 immigrant visas per fiscal year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: annualQuota Context triple: [Diversity Immigrant Visa, annualQuota, up to 55,000 immigrant visas per fiscal year]
-
A.
annualQuotaNumber
chosen
Indicates the specific numeric value assigned as an entity’s quota for a given year.
-
B.
dailyQuota
Indicates the maximum amount or limit allocated or allowed for an entity within a single day.
-
C.
isAnnual
Indicates that something occurs, is scheduled, or is valid once every year.
-
D.
annualFrom
Indicates that something recurs or is calculated on a yearly basis starting from a specified point in time.
-
E.
admissionQuota
Indicates a specified limit or allocation on the number of admissions allowed for a particular category, program, or period.
- 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_69d81c5ba13c8190839315f54768acfd |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02dc9f488190b7181dcb7e304632 |
completed | April 14, 2026, 9:03 a.m. |
| PD | Predicate disambiguation | batch_69dbc8691b608190a25a7c70a366b170 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:14 p.m.