Triple
T5939702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lakefield College School |
E132135
|
entity |
| Predicate | hasEnrollmentRange |
P67040
|
FINISHED |
| Object | approximately 350–450 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: approximately 350–450 students | Statement: [Lakefield College School, hasEnrollmentRange, approximately 350–450 students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnrollmentRange Context triple: [Lakefield College School, hasEnrollmentRange, approximately 350–450 students]
-
A.
hasStudentEnrollment
Indicates that a person or entity is enrolled as a student in a particular course, program, or educational institution.
-
B.
hasDegreeRange
Indicates that an entity is associated with a minimum and maximum degree value defining a range.
-
C.
hasRange
Indicates that a property or relation is constrained to take its values from a specified class, type, or value set.
-
D.
enrollmentLevel
Indicates the degree or status of participation an entity has in a particular enrollment context (such as a program, course, or service).
-
E.
enrolledIn
Indicates that one entity is formally registered as a participant in a course, program, or institution represented by another entity.
- F. None of above. chosen
Provenance (4 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_69c0085c55dc8190aa90e242c956e2fa |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03f26f51881908cc253fe5775a1fc |
completed | March 22, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69c03355caf08190b960563a1aed23f9 |
completed | March 22, 2026, 6:22 p.m. |
| PDg | Predicate description generation | batch_69c03f23dd20819089dbf0de0d913602 |
completed | March 22, 2026, 7:12 p.m. |
Created at: March 22, 2026, 4:01 p.m.