Triple
T19116368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 오세훈 |
E467917
|
entity |
| Predicate | educatedAt |
P5
|
FINISHED |
| Object | 서울대학교 법과대학 |
—
|
NE NERFINISHED |
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: 서울대학교 법과대학 | Statement: [오세훈, educatedAt, 서울대학교 법과대학]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 서울대학교 법과대학 Context triple: [오세훈, educatedAt, 서울대학교 법과대학]
-
A.
서울대학교 법학전문대학원
서울대학교 법학전문대학원은 대한민국을 대표하는 최고 수준의 법학 교육·연구 기관으로, 법조인과 법학자를 양성하는 서울대학교의 전문대학원이다.
-
B.
서울대학교 사범대학
서울대학교 사범대학은 서울대학교 소속으로 중등교원과 교육 전문가를 양성하는 대한민국의 대표적인 사범대학이다.
-
C.
SNU School of Law
chosen
SNU School of Law is the law faculty of Seoul National University and one of South Korea’s most prestigious institutions for legal education and research.
-
D.
Namseoul University
Namseoul University is a private higher education institution in South Korea known for its practical, industry-oriented programs and international exchange opportunities.
-
E.
Sogang University
Sogang University is a leading private research university in Seoul, South Korea, known for its strong humanities, social sciences, and business programs.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd06a26481908039e2a1bae8c597 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e3984bf48190818fa2b01b75decb |
completed | April 20, 2026, 8:28 a.m. |
Created at: April 10, 2026, 12:05 p.m.