Triple
T13857661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | H-1B specialty occupation visa |
E333105
|
entity |
| Predicate | capExemptEmployers |
P19424
|
FINISHED |
| Object | institutions of higher education |
—
|
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: institutions of higher education | Statement: [H-1B specialty occupation visa, capExemptEmployers, institutions of higher education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capExemptEmployers Context triple: [H-1B specialty occupation visa, capExemptEmployers, institutions of higher education]
-
A.
providesExemptionsTo
Indicates that one entity grants or offers exemptions, waivers, or exceptions from rules, obligations, or requirements to another entity.
-
B.
exemptedFrom
Indicates that an entity is not subject to, or is formally released from, a rule, obligation, requirement, or liability that would otherwise apply.
-
C.
exemptionType
Indicates the specific category or kind of exemption that applies in a given context.
-
D.
exemptedInstitutionType
Indicates that an institution belongs to a category or type that is exempt from a specified rule, requirement, or obligation.
-
E.
employersInclude
chosen
Indicates that a specified set or group of employers contains, as members, the employer or employers referenced by the other argument.
- 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.