Triple
T37915585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yonsei University digital media |
E945805
|
entity |
| Predicate | mayIncludeEducationLevel |
P97458
|
FINISHED |
| Object | graduate |
—
|
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: graduate | Statement: [Yonsei University digital media, mayIncludeEducationLevel, graduate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayIncludeEducationLevel Context triple: [Yonsei University digital media, mayIncludeEducationLevel, graduate]
-
A.
educationLevelsCovered
chosen
Indicates the range or specific levels of education that are included or addressed by something (such as a program, policy, or resource).
-
B.
requiresEducationIn
Indicates that one entity necessitates that another entity possess education or formal training in a specified field or discipline.
-
C.
requiresEducation
Indicates that performing or holding the related role, activity, or position depends on having a specified level or type of education.
-
D.
possibleDegreeLevel
Indicates the academic or qualification level that an entity can potentially attain, offer, or be associated with.
-
E.
hasEducationCharacteristic
Indicates that an entity possesses a specific educational attribute, quality, or feature (such as level, type, or status of education).
- 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_69f76ef2ebd88190be5229f2621070b3 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd166a488190b1bf9316b0790801 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:20 p.m.