Triple
T1334793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pusan National University |
E28722
|
entity |
| Predicate | numberOfUndergraduateStudents |
P3396
|
FINISHED |
| Object | over 20000 |
—
|
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 20000 | Statement: [Pusan National University, numberOfUndergraduateStudents, over 20000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfUndergraduateStudents Context triple: [Pusan National University, numberOfUndergraduateStudents, over 20000]
-
A.
undergraduateEnrollment
chosen
Indicates the number of undergraduate students enrolled in an institution or program.
-
B.
undergraduatesApprox
Indicates that the relationship involves an approximate or estimated number of undergraduate students associated with an entity.
-
C.
hasUndergraduatePrograms
Indicates that an educational institution offers one or more undergraduate-level academic programs.
-
D.
numberOfFaculties
Indicates the total count of faculties associated with a given entity.
-
E.
studentPopulationLevel
Indicates the relative size or magnitude of the student population associated with an entity.
- 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_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1eb119881909dd5fbf728d9e8ba |
completed | March 1, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69a4bef174708190a07bbc697fe19a2d |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:55 p.m.