Triple
T423978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tohoku University |
E8164
|
entity |
| Predicate | hasUndergraduateEnrollment |
P3396
|
FINISHED |
| Object | over 10,000 |
—
|
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 10,000 | Statement: [Tohoku University, hasUndergraduateEnrollment, over 10,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUndergraduateEnrollment Context triple: [Tohoku University, hasUndergraduateEnrollment, over 10,000]
-
A.
undergraduateEnrollment
chosen
Indicates the number of undergraduate students enrolled in an institution or program.
-
B.
hasStudentEnrollment
Indicates that a person or entity is enrolled as a student in a particular course, program, or educational institution.
-
C.
academicStatus
Indicates the educational or scholarly standing or level an entity holds within an academic context.
-
D.
undergraduateOnly
Indicates that the associated activity, course, or resource is restricted exclusively to undergraduate students.
-
E.
isStudiedIn
Indicates that a subject (such as a topic, field, or phenomenon) is examined, researched, or learned about within a particular context, environment, or discipline.
- 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eed3e4cc8190ba6aff3bd1adb06f |
completed | Feb. 28, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69a2edd5439c8190aea661b8b4aa51e9 |
completed | Feb. 28, 2026, 1:29 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.