Triple
T17805064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chan-sung Jung |
E444535
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Chan-sung 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: Chan-sung Jung | Statement: [Chan-sung Jung, name, Chan-sung Jung]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chan-sung Jung Context triple: [Chan-sung Jung, name, Chan-sung Jung]
-
A.
Chan-sung Jung
chosen
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.
-
B.
Sung-kyu Jung
Sung-kyu Jung is a notable individual recognized as a prominent bearer of the Korean surname Jung.
-
C.
Tae-sung Jeong
Tae-sung Jeong is a television producer best known for serving as an executive producer on the historical sci-fi drama series "Project Blue Book."
-
D.
Yong-jun Jung
Yong-jun Jung is a notable individual recognized for achievements significant enough to be distinctly associated with the surname Jung.
-
E.
Kwanghun Chung
Kwanghun Chung is a neuroscientist and bioengineer known for pioneering advanced tissue-clearing and imaging techniques that enable high-resolution, three-dimensional visualization of biological tissues.
- 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_69d8b9efe370819095cd219b143ae727 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4880385b48190b8dea0f05dfa1300 |
completed | April 19, 2026, 7:45 a.m. |
Created at: April 10, 2026, 10:14 a.m.