Triple
T13857530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EB-1 priority workers immigrant visa |
E333102
|
entity |
| Predicate | derivativeCategoryForSpouse |
P111816
|
FINISHED |
| Object | E-14 |
—
|
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: E-14 | Statement: [EB-1 priority workers immigrant visa, derivativeCategoryForSpouse, E-14]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: derivativeCategoryForSpouse Context triple: [EB-1 priority workers immigrant visa, derivativeCategoryForSpouse, E-14]
-
A.
spouseType
Indicates the specific role or category of a person within a spousal relationship (e.g., husband, wife, partner).
-
B.
associatedWithFieldThroughSpouse
Indicates that an entity is connected to a particular field or domain by virtue of their spouse’s involvement or association with that field.
-
C.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
-
D.
spouseInstanceOf
Indicates that one entity is the specific spouse (marriage partner) instance of another entity.
-
E.
granteeSpouse
Indicates that one person is the spouse of the person who receives a grant, transfer, or similar benefit.
- 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_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. |
| PDg | Predicate description generation | batch_69dcad0eea9881908f71e1eed9a2446b |
completed | April 13, 2026, 8:45 a.m. |
Created at: April 9, 2026, 10:14 p.m.