Triple
T19116362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 오세훈 |
E467917
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | Oh Se-hoon |
—
|
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: Oh Se-hoon | Statement: [오세훈, alternativeName, Oh Se-hoon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oh Se-hoon Context triple: [오세훈, alternativeName, Oh Se-hoon]
-
A.
Oh Se-hoon
chosen
Oh Se-hoon is a South Korean politician best known for serving multiple terms as the mayor of Seoul.
-
B.
Oh Seung-hwan
Oh Seung-hwan is a South Korean professional baseball relief pitcher renowned as one of the KBO League’s greatest closers and for his successful stints in Nippon Professional Baseball and Major League Baseball.
-
C.
Jeong Ji-hoon
Jeong Ji-hoon, better known by his stage name Rain, is a South Korean singer, actor, and music producer who gained international fame as a K-pop star and Hallyu icon.
-
D.
Oh Jae-won
Oh Jae-won is a South Korean former professional baseball infielder who played in the KBO League, most notably for the Doosan Bears.
-
E.
Oh Hyeon-gyu
Oh Hyeon-gyu is a South Korean professional footballer known for playing as a forward, including for the national team and in European club football.
- 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.