Triple
T34597112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lane College |
E888341
|
entity |
| Predicate | approximateUndergraduateEnrollment |
P3389
|
FINISHED |
| Object | around 1,000 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: around 1,000 students | Statement: [Lane College, approximateUndergraduateEnrollment, around 1,000 students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateUndergraduateEnrollment Context triple: [Lane College, approximateUndergraduateEnrollment, around 1,000 students]
-
A.
undergraduateEnrollment
Indicates the number of undergraduate students enrolled in an institution or program.
-
B.
hasApproximateStudents
Indicates that an entity is associated with an estimated or approximate number of students, rather than an exact count.
-
C.
hasFacultySizeApprox
Indicates that an institution has an approximate number of faculty members equal to the specified value.
-
D.
undergraduatesApprox
chosen
Indicates that the relationship involves an approximate or estimated number of undergraduate students associated with an entity.
-
E.
typicalEnrollment
Indicates the usual or standard number of participants or members enrolled in something, such as a course, program, or institution.
- 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_69f349d3bfcc81909874c99e646fb3ea |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff255b84788190a94682f4efe1d0b8 |
completed | May 9, 2026, 12:15 p.m. |
| PD | Predicate disambiguation | batch_69ff24f3ab108190bb017a656cff3d82 |
completed | May 9, 2026, 12:13 p.m. |
Created at: May 1, 2026, 2:03 a.m.