Triple
T3229717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adele Sherbert |
E67708
|
entity |
| Predicate | benefitProgramInvolved |
P46311
|
FINISHED |
| Object | state unemployment insurance |
—
|
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: state unemployment insurance | Statement: [Adele Sherbert, benefitProgramInvolved, state unemployment insurance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitProgramInvolved Context triple: [Adele Sherbert, benefitProgramInvolved, state unemployment insurance]
-
A.
benefitAdministered
Indicates that a benefit (such as aid, service, or entitlement) has been formally provided or delivered to an eligible recipient by an administering party.
-
B.
hasBenefit
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
-
C.
establishedProgram
Indicates that an entity has created and put into operation a formal program that is now in an active, ongoing state.
-
D.
benefitsOrganizationType
Indicates that something provides an advantage, support, or positive impact specifically to a particular type or category of organization.
-
E.
benefitsState
Indicates that one entity provides an advantage, improvement, or positive outcome to a state or governmental entity.
- 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_69ad858c61888190a31196310d9b30b5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaeb826588190a93bcfb1242310e7 |
completed | March 8, 2026, 5:15 p.m. |
| PD | Predicate disambiguation | batch_69ad9e0dc2248190a38c40f4e06cd41c |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada0f9259c8190afbc5ad0fa55436b |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:08 p.m.