Triple
T3684413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Ivies |
E78188
|
entity |
| Predicate | hasTypicalEnrollmentRange |
P30984
|
FINISHED |
| Object | approximately 1,500–3,000 undergraduates |
—
|
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: approximately 1,500–3,000 undergraduates | Statement: [Little Ivies, hasTypicalEnrollmentRange, approximately 1,500–3,000 undergraduates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalEnrollmentRange Context triple: [Little Ivies, hasTypicalEnrollmentRange, approximately 1,500–3,000 undergraduates]
-
A.
hasStudentEnrollment
Indicates that a person or entity is enrolled as a student in a particular course, program, or educational institution.
-
B.
hasTypicalFirstCohortSize
Indicates the usual or standard number of individuals in the first cohort associated with an entity.
-
C.
hasDegreeRange
Indicates that an entity is associated with a minimum and maximum degree value defining a range.
-
D.
hasApproximateStudents
chosen
Indicates that an entity is associated with an estimated or approximate number of students, rather than an exact count.
-
E.
typicalStudentStatus
Indicates the usual or standard enrollment or academic standing that a student typically holds within an educational context.
- 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_69ad85e18c1c8190be8aafb227f39f48 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc49644d08190866d6c5df9d2b48d |
completed | March 8, 2026, 6:48 p.m. |
| PD | Predicate disambiguation | batch_69adb84be1fc81909721c871babb4633 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:26 p.m.