Triple
T2826030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indiana State University |
E54922
|
entity |
| Predicate | enrollmentApproximate |
P30984
|
FINISHED |
| Object | more than 10,000 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: more than 10,000 students | Statement: [Indiana State University, enrollmentApproximate, more than 10,000 students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enrollmentApproximate Context triple: [Indiana State University, enrollmentApproximate, more than 10,000 students]
-
A.
hasApproximateStudents
chosen
Indicates that an entity is associated with an estimated or approximate number of students, rather than an exact count.
-
B.
enrollmentType
Indicates the specific category or mode under which an entity is enrolled in a program, service, or system.
-
C.
hasStudentEnrollment
Indicates that a person or entity is enrolled as a student in a particular course, program, or educational institution.
-
D.
enrollmentModel
Indicates the type or structure of the enrollment relationship that governs how entities (such as users or participants) are registered or associated with a program, course, or service.
-
E.
undergraduateEnrollment
Indicates the number of undergraduate students enrolled in an institution or program.
- 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_69ab49e100c0819082a40cb797383243 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde94ba848190b2c990936e07e6bb |
completed | March 7, 2026, 8:15 a.m. |
| PD | Predicate disambiguation | batch_69abdd0acab881909e8c25cbef83678c |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:59 p.m.