Triple
T1224190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Work-Study Program |
E26288
|
entity |
| Predicate | benefitToStudents |
P10669
|
FINISHED |
| Object | reduce need for student loans |
—
|
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: reduce need for student loans | Statement: [Federal Work-Study Program, benefitToStudents, reduce need for student loans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitToStudents Context triple: [Federal Work-Study Program, benefitToStudents, reduce need for student loans]
-
A.
educationalImpact
chosen
Indicates the effect or influence that one entity has on the learning, knowledge, or educational outcomes of another.
-
B.
targetStudentGroup
Indicates a relationship where something is directed, tailored, or intended specifically for a particular group of students.
-
C.
studentBodyFocus
Indicates that the primary attention, concern, or efforts are directed toward the student body as a whole.
-
D.
facultyStudentInteraction
Indicates interactions, communications, or engagements that occur between faculty members and students.
-
E.
studentsWing
Indicates a relationship where a particular wing, section, or area is designated for or associated with students.
- 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.