Triple
T1224181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Work-Study Program |
E26288
|
entity |
| Predicate | wageDeterminedBy |
P7593
|
FINISHED |
| Object | institutional policies and job type |
—
|
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: institutional policies and job type | Statement: [Federal Work-Study Program, wageDeterminedBy, institutional policies and job type]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wageDeterminedBy Context triple: [Federal Work-Study Program, wageDeterminedBy, institutional policies and job type]
-
A.
determinedBy
chosen
Indicates that one entity’s state, value, or outcome is decided, controlled, or fully specified by another entity.
-
B.
salaryType
Indicates the classification or structure of compensation associated with an entity, such as whether pay is salaried, hourly, commission-based, or another type.
-
C.
priceDeterminedBy
Indicates that the price of one entity is set, influenced, or calculated based on another entity or factor.
-
D.
salary
Indicates the amount of monetary compensation an entity receives, typically on a regular basis, for work or services performed.
-
E.
laborSystem
Indicates the type or structure of work organization, employment arrangements, and labor relations that govern how work is performed and managed.
- 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_69a49484688c8190a1bf285eb396a8b6 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be233fd88190996faf4105c0b8d7 |
completed | March 1, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69a4bb644af08190ba25905f20adb01a |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.