Triple
T1166850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Supplemental Security Income |
E24816
|
entity |
| Predicate | applicationMethod |
P859
|
FINISHED |
| Object | in-person application |
—
|
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: in-person application | Statement: [Supplemental Security Income, applicationMethod, in-person application]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: applicationMethod Context triple: [Supplemental Security Income, applicationMethod, in-person application]
-
A.
applicationLocation
Indicates the place or environment where an application is deployed, used, or made available.
-
B.
method
chosen
Indicates the technique, procedure, or process used by an entity to perform an action or achieve a result.
-
C.
hasApp
Indicates that an entity possesses, provides, or is associated with a particular application.
-
D.
APIType
Indicates the type or category of an API associated with or used by an entity.
-
E.
appliesFramework
Indicates that one entity uses or implements a particular framework in relation to another entity or context.
- 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bccd75048190b8ce88237c1a748b |
completed | March 1, 2026, 10:25 p.m. |
| PD | Predicate disambiguation | batch_69a4bb548c1481909092626c572d8782 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.