Triple
T1355294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Guelph |
E28974
|
entity |
| Predicate | hasUndergraduateStudents |
P3396
|
FINISHED |
| Object | over 23000 |
—
|
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: over 23000 | Statement: [University of Guelph, hasUndergraduateStudents, over 23000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUndergraduateStudents Context triple: [University of Guelph, hasUndergraduateStudents, over 23000]
-
A.
hasStudents
Indicates that an entity (such as a class, school, or teacher) is associated with one or more students.
-
B.
hasUndergraduatePrograms
Indicates that an educational institution offers one or more undergraduate-level academic programs.
-
C.
hasDoctoralStudents
Indicates that a person serves as the doctoral advisor or supervisor of one or more doctoral students.
-
D.
hasDoctoralPrograms
Indicates that an institution offers one or more doctoral-level academic degree programs.
-
E.
undergraduateEnrollment
chosen
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_69a498571d248190a0ac9eb02d97097f |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c28afc848190925d8b2f9aeac12d |
completed | March 1, 2026, 10:49 p.m. |
| PD | Predicate disambiguation | batch_69a4bef7700c819099b294e8d9320e70 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:56 p.m.