Triple
T41807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Toronto |
E826
|
entity |
| Predicate | undergraduatesApprox |
P3389
|
FINISHED |
| Object | 70000+ |
—
|
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: 70000+ | Statement: [University of Toronto, undergraduatesApprox, 70000+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: undergraduatesApprox Context triple: [University of Toronto, undergraduatesApprox, 70000+]
-
A.
university
Indicates that an educational institution of higher learning is associated with or attended by a given entity.
-
B.
academicAdvisor
Indicates that one entity serves as the academic advisor, providing formal guidance and oversight on academic matters, to another entity.
-
C.
campus
Indicates that an entity is located on, associated with, or taking place within a particular campus.
-
D.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
-
E.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24db9527c8190816b6b25c88cb2f4 |
completed | Feb. 28, 2026, 2:06 a.m. |
| PD | Predicate disambiguation | batch_69a24ab8a8908190beec6da6694dd4c9 |
completed | Feb. 28, 2026, 1:54 a.m. |
| PDg | Predicate description generation | batch_69a24db81c748190948560892f12c61b |
completed | Feb. 28, 2026, 2:06 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.