Triple
T1166853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Supplemental Security Income |
E24816
|
entity |
| Predicate | benefitPurpose |
P79
|
FINISHED |
| Object | help pay for food |
—
|
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: help pay for food | Statement: [Supplemental Security Income, benefitPurpose, help pay for food]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitPurpose Context triple: [Supplemental Security Income, benefitPurpose, help pay for food]
-
A.
benefits
Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or action.
-
B.
benefitForm
Indicates that one entity is a specific form, type, or variant in which a benefit is provided or realized for another entity.
-
C.
reasonForUse
Indicates that one entity specifies the justification, purpose, or motivation for using another entity.
-
D.
purpose
chosen
Indicates that one entity exists, is done, or is used in order to achieve, support, or serve the goal, function, or intended outcome of another entity.
-
E.
hasBenefit
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
- 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.