Triple
T6016749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Missouri System |
E133965
|
entity |
| Predicate | hasEnrollmentScope |
P67040
|
FINISHED |
| Object | tens of thousands of students |
—
|
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: tens of thousands of students | Statement: [University of Missouri System, hasEnrollmentScope, tens of thousands of students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnrollmentScope Context triple: [University of Missouri System, hasEnrollmentScope, tens of thousands of students]
-
A.
hasEnrollmentRange
chosen
Indicates that there is a specified minimum and/or maximum number of participants allowed or expected for an enrollment in a given context.
-
B.
hasStudentEnrollment
Indicates that a person or entity is enrolled as a student in a particular course, program, or educational institution.
-
C.
hasScope
Indicates that one entity defines, limits, or encompasses the range, extent, or applicability within which another entity operates or is valid.
-
D.
enrolledIn
Indicates that one entity is formally registered as a participant in a course, program, or institution represented by another entity.
-
E.
enrollmentLevel
Indicates the degree or status of participation an entity has in a particular enrollment context (such as a program, course, or service).
- 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_69c0087361a48190905c6b55969852b8 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04f82dd688190ad8882d8fb547cb5 |
completed | March 22, 2026, 8:22 p.m. |
| PD | Predicate disambiguation | batch_69c049e75b3881908be106fbcf8c68d4 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:06 p.m.