Triple
T24651667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Agency for Technical Relief |
E610265
|
entity |
| Predicate | hasPaidStaff |
P156913
|
FINISHED |
| Object | full-time 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: full-time employees | Statement: [Federal Agency for Technical Relief, hasPaidStaff, full-time employees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPaidStaff Context triple: [Federal Agency for Technical Relief, hasPaidStaff, full-time employees]
-
A.
hasStaffedHours
Indicates that specific hours or time periods are assigned during which staff are present and available.
-
B.
paidFor
Indicates that one entity provided payment to cover the cost of something on behalf of another entity.
-
C.
hasPayStatus
Indicates the current payment state or condition associated with an entity, such as whether an amount is paid, unpaid, pending, or otherwise resolved.
-
D.
hasPaidTransfer
Indicates that a transfer of something (such as money, ownership, or rights) has been completed through a payment.
-
E.
hadStaffRole
Indicates that an entity served in a specific staff role or position for another entity during some period.
- 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_69e2c4d350a481909170482bc2ce6af9 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f41011d8048190be70329ba0bfb7c7 |
completed | May 1, 2026, 2:29 a.m. |
| PD | Predicate disambiguation | batch_69f40ed9d47881909fcfc0d04e8d074a |
completed | May 1, 2026, 2:24 a.m. |
| PDg | Predicate description generation | batch_69f41010f06c81908ee7f773220df14f |
completed | May 1, 2026, 2:29 a.m. |
Created at: April 18, 2026, 2:34 a.m.