Triple
T3089183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Massachusetts College of Liberal Arts |
E64447
|
entity |
| Predicate | hasApproximateEnrollment |
P30984
|
FINISHED |
| Object | small enrollment |
—
|
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: small enrollment | Statement: [Massachusetts College of Liberal Arts, hasApproximateEnrollment, small enrollment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateEnrollment Context triple: [Massachusetts College of Liberal Arts, hasApproximateEnrollment, small enrollment]
-
A.
hasApproximateStudents
chosen
Indicates that an entity is associated with an estimated or approximate number of students, rather than an exact count.
-
B.
hasStudentEnrollment
Indicates that a person or entity is enrolled as a student in a particular course, program, or educational institution.
-
C.
undergraduateEnrollment
Indicates the number of undergraduate students enrolled in an institution or program.
-
D.
enrollmentType
Indicates the specific category or mode under which an entity is enrolled in a program, service, or system.
-
E.
hasStudents
Indicates that an entity (such as a class, school, or teacher) is associated with one or more 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_69ad857c97d88190b26f9b1c90839c77 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada20b99a4819090c3d3e08ed556ad |
completed | March 8, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69ad9ded78f881908be6fc0fb7c35764 |
completed | March 8, 2026, 4:03 p.m. |
Created at: March 8, 2026, 3:03 p.m.