Triple
T17816528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yong-jun Jung |
E444858
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Yong-jun Jung |
—
|
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: Yong-jun Jung | Statement: [Yong-jun Jung, name, Yong-jun Jung]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yong-jun Jung Context triple: [Yong-jun Jung, name, Yong-jun Jung]
-
A.
Yong-jun Jung
chosen
Yong-jun Jung is a notable individual recognized for achievements significant enough to be distinctly associated with the surname Jung.
-
B.
Sung-kyu Jung
Sung-kyu Jung is a notable individual recognized as a prominent bearer of the Korean surname Jung.
-
C.
Chan-sung Jung
Chan-sung Jung, widely known as "The Korean Zombie," is a South Korean mixed martial artist recognized for his exciting fighting style and success in top MMA promotions like the UFC.
-
D.
Yong-taek Jung
Yong-taek Jung is a notable individual recognized for bearing the Korean surname Jung.
-
E.
Woo-sung Jung
Woo-sung Jung is a prominent South Korean actor and film producer known for his leading roles in action and drama films such as "Beat," "The Good, the Bad, the Weird," and "Steel Rain."
- 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_69d8b9f0de78819099395b14db75a8a6 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4887f7d048190b6d813b9f0fab3e7 |
completed | April 19, 2026, 7:47 a.m. |
Created at: April 10, 2026, 10:14 a.m.