Triple
T22473445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Na Hong-jin |
E555563
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Na Hong-jin |
—
|
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: Na Hong-jin | Statement: [Na Hong-jin, name, Na Hong-jin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Na Hong-jin Context triple: [Na Hong-jin, name, Na Hong-jin]
-
A.
Na Hong-jin
chosen
Na Hong-jin is a South Korean filmmaker renowned for his intense, genre-blending thrillers such as "The Chaser," "The Yellow Sea," and "The Wailing."
-
B.
Hong Joon-pyo
Hong Joon-pyo is a South Korean conservative politician who has served as governor of South Gyeongsang Province and as a prominent national lawmaker and party leader.
-
C.
Hwang Jang-lee
Hwang Jang-lee is a Korean martial artist and actor famed for his villainous kicking roles in classic Hong Kong kung fu films.
-
D.
Lee Man-hee
Lee Man-hee was a pioneering South Korean film director renowned for his influential and stylistically innovative works during the Golden Age of Korean cinema in the 1960s.
-
E.
Chung Mong-koo
Chung Mong-koo is a South Korean businessman best known as the longtime chairman who transformed Hyundai Motor Group into one of the world’s largest automotive manufacturers.
- 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_69e11e52c2048190952dc5df209b9bed |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15be2034c81909d1263f2ed114b46 |
completed | April 29, 2026, 1:16 a.m. |
Created at: April 16, 2026, 8:49 p.m.