Triple
T37789315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Civil Service Retirement and Disability Fund |
E942037
|
entity |
| Predicate | benefitProgramFor |
P101952
|
FINISHED |
| Object | civilian federal employees |
—
|
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: civilian federal employees | Statement: [Civil Service Retirement and Disability Fund, benefitProgramFor, civilian federal employees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitProgramFor Context triple: [Civil Service Retirement and Disability Fund, benefitProgramFor, civilian federal employees]
-
A.
benefitProgramInvolved
Indicates that a benefit program participates in, is associated with, or plays a role in the referenced situation or relationship.
-
B.
benefitAppliesTo
chosen
Indicates that a particular benefit is applicable to, or valid for, a specified entity or context.
-
C.
benefitAvailableAt
Indicates that a particular benefit can be obtained, accessed, or used at a specified location, time, or context.
-
D.
benefitsAre
Indicates that certain advantages, gains, or positive outcomes are possessed by or accrue to a particular entity or group.
-
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_69f76ee5cb0c81909a363d1c929156c0 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbb9e8108c8190ae1c7940b1677e95 |
completed | May 6, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fbb141605c8190b9c27d70352522db |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:19 p.m.